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ORCIDPhilip S. Yu
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- affiliation: University of Illinois at Chicago, Department of Computer Science, Chicago, IL, USA
- affiliation (PhD): Stanford University, Stanford, CA, USA
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2020 – today
- 2026
[j673]Lingzhe Zhang
, Tong Jia, Mengxi Jia, Yifan Wu, Aiwei Liu, Yong Yang, Zhonghai Wu, Xuming Hu, Philip S. Yu, Ying Li:
A Survey of AIOps in the Era of Large Language Models. ACM Comput. Surv. 58(2): 44:1-44:35 (2026)- [j672]Shang Wang, Tianqing Zhu, Bo Liu, Ming Ding, Dayong Ye, Wanlei Zhou, Philip S. Yu:
Unique Security and Privacy Threats of Large Language Models: A Comprehensive Survey. ACM Comput. Surv. 58(4): 83:1-83:36 (2026) - [j671]Feng He, Tianqing Zhu, Dayong Ye, Bo Liu, Wanlei Zhou, Philip S. Yu:
The Emerged Security and Privacy of LLM Agent: A Survey with Case Studies. ACM Comput. Surv. 58(6): 162:1-162:36 (2026) - [j670]Panpan Meng, Chenxu Wang, Shihao Wang, Kay Liu, Yankai Chen, Zhanggong Wang, Philip S. Yu:
Community-aware multi-granularity contrastive learning for graph anomaly detection. Expert Syst. Appl. 305: 130872 (2026) - [j669]Wensheng Gan, Zhenyao Ning, Zhenlian Qi, Philip S. Yu:
Mixture of experts (MoE): A big data perspective. Inf. Fusion 127: 103664 (2026) - [j668]Jibing Gong, Jiquan Peng, Wei Wang, Wei Zhou, Chaozhuo Li, Philip S. Yu:
Beyond embedding-mapping: Social network alignment via generative information fusion and LLM-guided iterative mechanism. Inf. Fusion 127: 103733 (2026) - [j667]Mingying Xu, Fei Hou, Jie Liu, Mengmei Zhang, Lei Shi, Feifei Kou, Lei Guo, Philip S. Yu, Xuming Hu:
Multimodal named entity recognition in the era of large pre-trained models: A comprehensive survey. Inf. Fusion 127: 103767 (2026) - [j666]Qingfeng Zhou, Wensheng Gan, Zhenlian Qi, Philip S. Yu:
Utility-Based Privacy-Preserving Data Mining. IEEE Internet Things J. 13(2): 2067-2084 (2026) - [j665]Yiting Huang, Yu-Ming Shang, Wei Huang, Sanchuan Guo, Jinhu Chen, Xi Zhang, Philip S. Yu:
Discovering new intents via spatio-temporal pseudo-label denoising. Inf. Process. Manag. 63(2): 104381 (2026) - [j664]Zeyu Zhang, Lu Li, Xingyu Ji, Kaiqi Zhao, Xiaofeng Zhu, Philip S. Yu, Jiawei Li, Maojun Wang:
Enhancing signed graph neural networks through curriculum-based training. Neural Networks 193: 107975 (2026) - [j663]Bo Yu, Jiuman Song, Lele Cong, Xianling Cong, Jouke Dijkstra, Philip S. Yu, Hechang Chen:
A prompt-aware knowledge-tuning framework for histopathology subtype classification with scarce annotation. Neural Networks 193: 107993 (2026) - [j662]Ling Huang, Zhe-Yuan Li, Xiao-Dong Huang, Yuefang Gao, Chang-Dong Wang, Philip S. Yu:
Autoencoder-based contrastive learning for next basket recommendation. Neural Networks 194: 108166 (2026) - [j661]Lixiang Xu, Xianwei Ding, Xin Yuan, Zhanlong Wang, Lu Bai, Enhong Chen, Philip S. Yu, Yuanyan Tang:
Improving Question Embeddings With Cognitive Representation Optimization for Knowledge Tracing. IEEE Trans. Cybern. 56(1): 235-248 (2026) - [j660]Junyou Zhu, Christian Nauck, Michael Lindner, Langzhou He, Philip S. Yu, Klaus-Robert Müller, Jürgen Kurths, Frank Hellmann:
Network Measure-Enriched GNNs: A New Framework for Power Grid Stability Prediction. IEEE Trans. Knowl. Data Eng. 38(1): 518-531 (2026) - [j659]Qihua Feng, Chunhui Duan, Jiawei Xue, Chaozhuo Li, Feiran Huang, Xi Zhang, Jian Weng, Philip S. Yu:
Imbalanced Semi-Supervised Learning for WiFi Gesture Recognition via Dynamic Threshold-Based Spatio-Temporal Attention Networks. IEEE Trans. Mob. Comput. 25(1): 483-499 (2026) - [e40]Feida Zhu, Philip S. Yu, Akiyo Nadamoto, Ee-Peng Lim, Kyuseok Shim, Wei Ding, Bingxue Zhang:
Database Systems for Advanced Applications - 30th International Conference, DASFAA 2025, Singapore, Singapore, May 26-29, 2025, Proceedings, Part II. Lecture Notes in Computer Science 15987, Springer 2026, ISBN 978-981-95-3829-4 [contents] - [e39]Feida Zhu, Philip S. Yu, Akiyo Nadamoto, Ee-Peng Lim, Kyuseok Shim, Wei Ding, Bingxue Zhang:
Database Systems for Advanced Applications - 30th International Conference, DASFAA 2025, Singapore, Singapore, May 26-29, 2025, Proceedings, Part III. Lecture Notes in Computer Science 15988, Springer 2026, ISBN 978-981-95-3905-5 [contents] - [e38]Feida Zhu, Philip S. Yu, Akiyo Nadamoto, Ee-peng Lim, Kyuseok Shim, Wei Ding, Bingxue Zhang:
Database Systems for Advanced Applications - 30th International Conference, DASFAA 2025, Singapore, Singapore, May 26-29, 2025, Proceedings, Part V. Lecture Notes in Computer Science 15990, Springer 2026, ISBN 978-981-95-4154-6 [contents] - [e37]Feida Zhu, Philip S. Yu, Akiyo Nadamoto, Ee-Peng Lim, Kyuseok Shim, Wei Ding, Bingxue Zhang:
Database Systems for Advanced Applications - 30th International Conference, DASFAA 2025, Singapore, Singapore, May 26-29, 2025, Proceedings, Part VI. Lecture Notes in Computer Science 15991, Springer 2026, ISBN 978-981-95-4157-7 [contents] - 2025
- [j658]Zhilin Zhao, Longbing Cao, Philip S. Yu:
Out-of-distribution detection by regaining lost clues. Artif. Intell. 339: 104275 (2025) - [j657]Yue Xing, Wensheng Gan, Qidi Chen, Philip S. Yu:
AI-generated content in landscape architecture: A survey. AI Open 6: 220-243 (2025) - [j656]Haishuai Wang, Yang Gao, Xin Zheng, Peng Zhang, Jiajun Bu, Philip S. Yu:
Graph neural architecture search with large language models. Sci. China Inf. Sci. 68(12) (2025) - [j655]Aiwei Liu, Leyi Pan, Yijian Lu, Jingjing Li, Xuming Hu, Xi Zhang, Lijie Wen, Irwin King, Hui Xiong, Philip S. Yu:
A Survey of Text Watermarking in the Era of Large Language Models. ACM Comput. Surv. 57(2): 47:1-47:36 (2025) - [j654]Yihan Cao, Siyu Li, Yixin Liu, Zhiling Yan, Yutong Dai, Philip S. Yu, Lichao Sun:
A Survey of AI-Generated Content (AIGC). ACM Comput. Surv. 57(5): 125:1-125:38 (2025) - [j653]Haopeng Zhang, Philip S. Yu, Jiawei Zhang:
A Systematic Survey of Text Summarization: From Statistical Methods to Large Language Models. ACM Comput. Surv. 57(11): 277:1-277:41 (2025) - [j652]Xi Zhu, Yu Wang, Hang Gao, Wujiang Xu, Chen Wang, Zhiwei Liu, Kun Wang, Mingyu Jin, Linsey Pang, Qingsong Weng, Philip S. Yu, Yongfeng Zhang:
Recommender Systems Meet Large Language Model Agents: A Survey. Found. Trends Priv. Secur. 7(4): 247-396 (2025) - [j651]Laiqiao Qin, Tianqing Zhu, Wanlei Zhou, Philip S. Yu:
Knowledge Distillation in Federated Learning: A Survey on Long Lasting Challenges and New Solutions. Int. J. Intell. Syst. 2025(1) (2025) - [j650]Chaoguang Luo, Liuying Wen, Yong Qin, Philip S. Yu, Liangwei Yang, Zhineng Hu:
Diversified recommendation with weighted hypergraph embedding: Case study in music. Neurocomputing 616: 128905 (2025) - [j649]Litian Zhang, Xiaoming Zhang, Ziyi Zhou, Xi Zhang, Philip S. Yu, Chaozhuo Li:
Knowledge-aware multimodal pre-training for fake news detection. Inf. Fusion 114: 102715 (2025) - [j648]Jia-Hao Syu, Jerry Chun-Wei Lin, Philip S. Yu:
Multi-head learning models for power consumption prediction of unmanned ground vehicles. Inf. Fusion 118: 102895 (2025) - [j647]Qihua Feng, Zhixun Lu, Chaozhuo Li, Feiran Huang, Jian Weng, Philip S. Yu:
End-to-end privacy-preserving image retrieval in cloud computing via anti-perturbation attentive token-aware vision transformer. Inf. Fusion 121: 103153 (2025) - [j646]Lixiang Xu, Kang Jiang, Xin Niu, Enhong Chen, Bin Luo, Philip S. Yu:
GL-BKGNN: Graphlet-based Bi-Kernel Interpretable Graph Neural Networks. Inf. Fusion 123: 103284 (2025) - [j645]Tie Li, Gang Kou, Yi Peng, Philip S. Yu:
Feature Selection and Grouping Effect Analysis for Credit Evaluation via Regularized Diagonal Distance Metric Learning. INFORMS J. Comput. 37(5): 1391-1412 (2025) - [j644]Hengzhu Liu, Ping Xiong, Tianqing Zhu, Philip S. Yu:
A survey on machine unlearning: Techniques and new emerged privacy risks. J. Inf. Secur. Appl. 90: 104010 (2025) - [j643]Chunkai Zhang, Yao Lu, Yuting Yang, Ryan Han-Yuan Zhang, Wensheng Gan, Philip S. Yu:
Mining high utility contrast patterns in sequences. Knowl. Inf. Syst. 67(11): 9947-9985 (2025) - [j642]Han Chen, Hairong Wang, Zhipeng Liu, Yuhua Li, Yifan Hu, Yujing Zhang, Kai Shu, Ruixuan Li, Philip S. Yu:
Multi-modal Robustness Fake News Detection with Cross-Modal and Propagation Network Contrastive Learning. Knowl. Based Syst. 309: 112800 (2025) - [j641]Jiayang Wu, Wensheng Gan, Jiahao Zhang, Philip S. Yu:
Contrastive learning for anomaly detection in hierarchical subgraph. Knowl. Based Syst. 317: 113435 (2025) - [j640]Junsan Zhang, Yuxue Liu, Mingwen Shao, Chenglizhao Chen, Zixuan Wang, Junliang Li, Yao Wan, Philip S. Yu:
Dual-level semantic collaboration and inference network for medical image report generation. Knowl. Based Syst. 328: 114278 (2025) - [j639]Yanxin Zheng, Wensheng Gan, Zefeng Chen, Zhenlian Qi, Qian Liang, Philip S. Yu:
Large language models for medicine: a survey. Int. J. Mach. Learn. Cybern. 16(2): 1015-1040 (2025) - [j638]Hong Lin, Wensheng Gan, Gengsen Huang, Philip S. Yu:
Towards high-utility sequential rules with repetitive items. Int. J. Mach. Learn. Cybern. 16(10): 7729-7745 (2025) - [j637]Ce Zhou, Qian Li, Chen Li, Jun Yu, Yixin Liu, Guangjing Wang, Kai Zhang, Cheng Ji, Qiben Yan, Lifang He, Hao Peng, Jianxin Li, Jia Wu, Ziwei Liu, Pengtao Xie, Caiming Xiong, Jian Pei, Philip S. Yu, Lichao Sun:
A comprehensive survey on pretrained foundation models: a history from BERT to ChatGPT. Int. J. Mach. Learn. Cybern. 16(12): 9851-9915 (2025) - [j636]Fanlong Zeng, Wensheng Gan, Yongheng Wang, Philip S. Yu:
Distributed training of large language models: A survey. Nat. Lang. Process. J. 12: 100174 (2025) - [j635]Runliang Niu, Qi Wang, He Kong, Qianli Xing, Yi Chang, Philip S. Yu:
Learn to explain transformer via interpretation path by reinforcement learning. Neural Networks 188: 107496 (2025) - [j634]Xiaoyan Yu, Jiaqian Ren, Lei Jiang, Hao Peng, Zhifeng Hao, Li Sun, Kun Peng, Liehuang Zhu, Philip S. Yu:
PromptSED: An evolving topic-enhanced prompting framework for incremental social event detection. Neural Networks 191: 107772 (2025) - [j633]Linlin Wang, Tianqing Zhu, Wanlei Zhou, Philip S. Yu:
Linkage on security, privacy and fairness in federated learning: New balances and new perspectives. Neural Networks 192: 107874 (2025) - [j632]Jiawei Liu, Cheng Yang, Zhiyuan Lu, Junze Chen, Yibo Li, Mengmei Zhang, Ting Bai, Yuan Fang, Lichao Sun, Philip S. Yu, Chuan Shi:
Graph Foundation Models: Concepts, Opportunities and Challenges. IEEE Trans. Pattern Anal. Mach. Intell. 47(6): 5023-5044 (2025) - [j631]Libo Qin, Qiguang Chen, Yuhang Zhou, Zhi Chen, Yinghui Li, Lizi Liao, Min Li, Wanxiang Che, Philip S. Yu:
A survey of multilingual large language models. Patterns 6(1): 101118 (2025) - [j630]Lixiang Xu, Zhiwen Wang, Lu Bai, Shengwei Ji, Bing Ai, Xiaofeng Wang, Philip S. Yu:
Multi-Level Knowledge Distillation with Positional Encoding Enhancement. Pattern Recognit. 163: 111458 (2025) - [j629]Jiayang Wu, Wensheng Gan, Jiahao Zhang, Philip S. Yu:
ADKGD: Anomaly Detection in Knowledge Graphs with Dual-Channel Training. ACM Trans. Asian Low Resour. Lang. Inf. Process. 24(11): 122:1-122:29 (2025) - [j628]Heng Xu, Tianqing Zhu, Lefeng Zhang, Wanlei Zhou, Philip S. Yu:
Update Selective Parameters: Federated Machine Unlearning Based on Model Explanation. IEEE Trans. Big Data 11(2): 524-539 (2025) - [j627]Huiqiang Chen, Tianqing Zhu, Bo Liu, Wanlei Zhou, Philip S. Yu:
Fine-Tuning a Biased Model for Improving Fairness. IEEE Trans. Big Data 11(3): 1397-1410 (2025) - [j626]Huan Tian, Bo Liu, Tianqing Zhu, Wanlei Zhou, Philip S. Yu:
Distilling Fair Representations From Fair Teachers. IEEE Trans. Big Data 11(3): 1419-1433 (2025) - [j625]Faqian Guan, Tianqing Zhu, Hui Sun, Wanlei Zhou, Philip S. Yu:
Large Language Models for Link Stealing Attacks Against Graph Neural Networks. IEEE Trans. Big Data 11(4): 1879-1893 (2025) - [j624]Faqian Guan, Tianqing Zhu, Wanlei Zhou, Philip S. Yu:
Topology-Based Node-Level Membership Inference Attacks on Graph Neural Networks. IEEE Trans. Big Data 11(5): 2809-2826 (2025) - [j623]Xiao-Dong Huang, Ling Huang, Yuefang Gao, Zhe-Yuan Li, Pei-Yuan Lai, Chang-Dong Wang, Philip S. Yu:
Knowledge-Aware Graph Prompt Tuning for Cross-Domain Recommendation. IEEE Trans. Comput. Soc. Syst. 12(6): 3923-3937 (2025) - [j622]Jian Zhu, Xiaoye Chen, Wensheng Gan, Zefeng Chen, Philip S. Yu:
Targeted Mining Precise-Positioning Episode Rules. IEEE Trans. Emerg. Top. Comput. Intell. 9(1): 904-917 (2025) - [j621]Zhi Li, Chaozhuo Li, Feiran Huang, Xi Zhang, Jian Weng, Philip S. Yu:
LapGLP: Approximating Infinite-Layer Graph Convolutions With Laplacian for Federated Recommendation. IEEE Trans. Inf. Forensics Secur. 20: 8178-8193 (2025) - [j620]Jiayang Wu, Wensheng Gan, Huashen Lu, Philip S. Yu:
Graph Contrastive Learning on Multi-label Classification for Recommendations. ACM Trans. Intell. Syst. Technol. 16(4): 77:1-77:19 (2025) - [j619]Zhixiao Wang, Jiayu Zhao, Chengcheng Sun, Xiaobin Rui, Philip S. Yu:
A General Concave Fairness Framework for Influence Maximization Based on Poverty Reward. ACM Trans. Knowl. Discov. Data 19(1): 14:1-14:23 (2025) - [j618]Hao Yan, Senzhang Wang, Chaozhuo Li, Jun Yin, Philip S. Yu, Jianxin Wang:
Have Our Cake and Eat It: Augmentation Diversity and Semantic Consistency Balanced Graph Contrastive Learning. ACM Trans. Knowl. Discov. Data 19(4): 1-25 (2025) - [j617]Jin-Jie Qiu, Shengda Zhuo, Philip S. Yu, Chang-Dong Wang, Shuqiang Huang:
Online Learning for Noisy Labeled Streams. ACM Trans. Knowl. Discov. Data 19(6): 1-29 (2025) - [j616]Gengsen Huang, Wensheng Gan, Philip S. Yu:
Towards Sequence Utility Maximization under Utility Occupancy Measure. ACM Trans. Knowl. Discov. Data 19(7): 126:1-126:27 (2025) - [j615]Guangjie Zeng, Hao Peng, Angsheng Li, Jia Wu, Chunyang Liu, Philip S. Yu:
Scalable Semi-Supervised Clustering via Structural Entropy With Different Constraints. IEEE Trans. Knowl. Data Eng. 37(1): 478-492 (2025) - [j614]Litian Zhang, Xiaoming Zhang, Ziyi Zhou, Xi Zhang, Senzhang Wang, Philip S. Yu, Chaozhuo Li:
Early Detection of Multimodal Fake News via Reinforced Propagation Path Generation. IEEE Trans. Knowl. Data Eng. 37(2): 613-625 (2025) - [j613]Runze Yang, Hao Peng, Angsheng Li, Peng Li, Chunyang Liu, Philip S. Yu:
Hierarchical Abstracting Graph Kernel. IEEE Trans. Knowl. Data Eng. 37(2): 724-738 (2025) - [j612]Zeyu Zhang, Chaozhuo Li, Xu Chen, Xing Xie, Philip S. Yu:
Meta Recommendation With Robustness Improvement. IEEE Trans. Knowl. Data Eng. 37(2): 781-793 (2025) - [j611]Lu Bai, Lixin Cui, Ming Li, Peng Ren, Yue Wang, Lichi Zhang, Philip S. Yu, Edwin R. Hancock:
AEGK: Aligned Entropic Graph Kernels Through Continuous-Time Quantum Walks. IEEE Trans. Knowl. Data Eng. 37(3): 1064-1078 (2025) - [j610]Ya-Wen Teng, Yishuo Shi, De-Nian Yang, Chih-Hua Tai, Philip S. Yu, Ming-Syan Chen:
Multi-Grade Revenue Maximization for Promotional and Competitive Viral Marketing in Social Networks. IEEE Trans. Knowl. Data Eng. 37(3): 1339-1353 (2025) - [j609]Juyong Jiang, Peiyan Zhang, Yingtao Luo, Chaozhuo Li, Jae Boum Kim, Kai Zhang, Senzhang Wang, Sunghun Kim, Philip S. Yu:
Improving Sequential Recommendations via Bidirectional Temporal Data Augmentation With Pre-Training. IEEE Trans. Knowl. Data Eng. 37(5): 2652-2664 (2025) - [j608]Songwei Zhao, Bo Yu, Kang Yang, Sinuo Zhang, Jifeng Hu, Yuan Jiang, Philip S. Yu, Hechang Chen:
A Flexible Diffusion Convolution for Graph Neural Networks. IEEE Trans. Knowl. Data Eng. 37(6): 3118-3131 (2025) - [j607]Wensheng Gan, Gengsen Huang, Jian Weng, Tianlong Gu, Philip S. Yu:
Towards Target Sequential Rules. IEEE Trans. Knowl. Data Eng. 37(6): 3766-3780 (2025) - [j606]Xiaobin Rui, Zhixiao Wang, Hao Peng, Wei Chen, Philip S. Yu:
A Scalable Algorithm for Fair Influence Maximization With Unbiased Estimator. IEEE Trans. Knowl. Data Eng. 37(7): 3881-3895 (2025) - [j605]Zhangtao Cheng, Yang Liu, Ting Zhong, Kunpeng Zhang, Fan Zhou, Philip S. Yu:
Disentangling Inter- and Intra-Cascades Dynamics for Information Diffusion Prediction. IEEE Trans. Knowl. Data Eng. 37(8): 4548-4563 (2025) - [j604]Qitong Liu, Hao Peng, Xiang Huang, Zhifeng Hao, Qingyun Sun, Zhengtao Yu, Philip S. Yu:
Hierarchical Text Classification Optimization via Structural Entropy and Singular Smoothing. IEEE Trans. Knowl. Data Eng. 37(9): 5283-5297 (2025) - [j603]Songwei Zhao, Bo Yu, Sinuo Zhang, Zhejian Yang, Jifeng Hu, Philip S. Yu, Hechang Chen:
EGNN: Exploring Structure-Level Neighborhoods in Graphs With Varying Homophily Ratios. IEEE Trans. Knowl. Data Eng. 37(10): 5852-5865 (2025) - [j602]Hao Miao, Ronghui Xu, Yan Zhao, Senzhang Wang, Jianxin Wang, Philip S. Yu, Christian S. Jensen:
A Parameter-Efficient Federated Framework for Streaming Time Series Anomaly Detection via Lightweight Adaptation. IEEE Trans. Mob. Comput. 24(9): 8872-8885 (2025) - [j601]Zefeng Chen, Wensheng Gan, Gengsen Huang, Zhenlian Qi, Yan Li, Philip S. Yu:
TALENT: Targeted Mining of Non-overlapping Sequential Patterns. ACM Trans. Manag. Inf. Syst. 16(4): 31:1-31:34 (2025) - [j600]Wenjing Chang, Kay Liu, Philip S. Yu, Jianjun Yu:
Enhancing Fairness in Unsupervised Graph Anomaly Detection through Disentanglement. Trans. Mach. Learn. Res. 2025 (2025) - [j599]Haoyan Xu, Kay Liu, Zhengtao Yao, Philip S. Yu, Mengyuan Li, Kaize Ding, Yue Zhao:
LEGO-Learn: Label-Efficient Graph Open-Set Learning. Trans. Mach. Learn. Res. 2025 (2025) - [j598]Huan Tian, Bo Liu, Tianqing Zhu, Wanlei Zhou, Philip S. Yu:
MultiFair: Model Fairness With Multiple Sensitive Attributes. IEEE Trans. Neural Networks Learn. Syst. 36(3): 5654-5667 (2025) - [j597]Yazhou Ren, Jingyu Pu, Zhimeng Yang, Jie Xu, Guofeng Li, Xiaorong Pu, Philip S. Yu, Lifang He:
Deep Clustering: A Comprehensive Survey. IEEE Trans. Neural Networks Learn. Syst. 36(4): 5858-5878 (2025) - [j596]Xusheng Zhao, Qiong Dai, Xu Bai, Jia Wu, Hao Peng, Huailiang Peng, Zhengtao Yu, Philip S. Yu:
Reinforced GNNs for Multiple Instance Learning. IEEE Trans. Neural Networks Learn. Syst. 36(4): 6693-6707 (2025) - [j595]Phu Pham, Quang-Thinh Bui, Ngoc Thanh Nguyen, Robert Kozma, Philip S. Yu, Bay Vo:
Topological Data Analysis in Graph Neural Networks: Surveys and Perspectives. IEEE Trans. Neural Networks Learn. Syst. 36(6): 9758-9776 (2025) - [j594]Jianpeng Chen, Yawen Ling, Jie Xu, Yazhou Ren, Shudong Huang, Xiaorong Pu, Zhifeng Hao, Philip S. Yu, Lifang He:
Variational Graph Generator for Multiview Graph Clustering. IEEE Trans. Neural Networks Learn. Syst. 36(6): 11078-11091 (2025) - [j593]Ling Huang, Dong Huang, Han Zou, Yuefang Gao, Chang-Dong Wang, Philip S. Yu:
Knowledge-Reinforced Cross-Domain Recommendation. IEEE Trans. Neural Networks Learn. Syst. 36(7): 12880-12894 (2025) - [j592]Zheng Wang, Hongming Ding, Li Pan, Jianhua Li, Zhiguo Gong, Philip S. Yu:
From Cluster Assumption to Graph Convolution: Graph-Based Semi-Supervised Learning Revisited. IEEE Trans. Neural Networks Learn. Syst. 36(7): 12952-12963 (2025) - [j591]Xiaoye Chen, Wensheng Gan, Zefeng Chen, Jian Zhu, Ruichu Cai, Philip S. Yu:
Toward Targeted Mining of RFM Patterns. IEEE Trans. Neural Networks Learn. Syst. 36(9): 16619-16632 (2025) - [j590]Pu Li, Xiaoyan Yu, Hao Peng, Yantuan Xian, Linqin Wang, Li Sun, Jingyun Zhang, Philip S. Yu:
Relational Prompt-Based Pre-Trained Language Models for Social Event Detection. ACM Trans. Inf. Syst. 43(1): 12:1-12:43 (2025) - [j589]Zhiwei Liu, Hao Peng, Caiming Xiong, Julian J. McAuley, Philip S. Yu:
Introduction to the Special Issue on Knowledge Transferring for Recommender Systems. Trans. Recomm. Syst. 3(3): 26:1-26:4 (2025) - [j588]Qihua Feng, Zhixun Lu, Litian Zhang, Chaozhuo Li, Feiran Huang, Jian Weng, Philip S. Yu:
Privacy-Preserving Image Retrieval in Cloud Computing via Adaptive Secret Keys and Self-Supervised Block-Augmented Pretraining. IEEE Trans. Serv. Comput. 18(4): 2310-2325 (2025) - [j587]Yang Wu, Yao Wan, Zhaoyang Chu, Wenting Zhao, Ye Liu, Hongyu Zhang, Xuanhua Shi, Hai Jin, Philip S. Yu:
Can Large Language Models Serve as Evaluators for Code Summarization? IEEE Trans. Software Eng. 51(12): 3205-3217 (2025) - [c1155]Li Sun, Ziheng Zhang, Zixi Wang, Yujie Wang, Qiqi Wan, Hao Li, Hao Peng, Philip S. Yu:
Pioneer: Physics-informed Riemannian Graph ODE for Entropy-increasing Dynamics. AAAI 2025: 12586-12594 - [c1154]Xiaoyan Yu, Yifan Wei, Shuaishuai Zhou, Zhiwei Yang, Li Sun, Hao Peng, Liehuang Zhu, Philip S. Yu:
Towards Effective, Efficient and Unsupervised Social Event Detection in the Hyperbolic Space. AAAI 2025: 13106-13114 - [c1153]Xiang Huang, Hao Peng, Li Sun, Hui Lin, Chunyang Liu, Jiang Cao, Philip S. Yu:
Structural Entropy Guided Probabilistic Coding. AAAI 2025: 17467-17475 - [c1152]Xiuxuan Shen, Zhongyuan Jiang, Junsan Zhang, Junxiao Han, Yao Wan, Chengjie Guo, Bingcheng Liu, Jie Wu, Renxiang Li, Philip S. Yu:
ProvBench: A Benchmark of Legal Provision Recommendation for Contract Auto-Reviewing. ACL (1) 2025: 6240-6254 - [c1151]Lingwei Wei, Dou Hu, Wei Zhou, Philip S. Yu, Songlin Hu:
Structure-adaptive Adversarial Contrastive Learning for Multi-Domain Fake News Detection. ACL (Findings) 2025: 9739-9752 - [c1150]Leyi Pan, Aiwei Liu, Shiyu Huang, Yijian Lu, Xuming Hu, Lijie Wen, Irwin King, Philip S. Yu:
Can LLM Watermarks Robustly Prevent Unauthorized Knowledge Distillation? ACL (1) 2025: 13228-13251 - [c1149]Liancheng Fang, Aiwei Liu, Hengrui Zhang, Henry Peng Zou, Weizhi Zhang, Philip S. Yu:
TABGEN-ICL: Residual-Aware In-Context Example Selection for Tabular Data Generation. ACL (Findings) 2025: 20027-20041 - [c1148]Yujie Feng, Xujia Wang, Zexin Lu, Shenghong Fu, Guangyuan Shi, Yongxin Xu, Yasha Wang, Philip S. Yu, Xu Chu, Xiao-Ming Wu:
Recurrent Knowledge Identification and Fusion for Language Model Continual Learning. ACL (1) 2025: 27396-27413 - [c1147]Henry Peng Zou, Zhengyao Gu, Yue Zhou, Yankai Chen, Weizhi Zhang, Liancheng Fang, Yibo Wang, Yangning Li, Kay Liu, Philip S. Yu:
TestNUC: Enhancing Test-Time Computing Approaches and Scaling through Neighboring Unlabeled Data Consistency. ACL (1) 2025: 30750-30762 - [c1146]Kun Peng, Cong Cao, Hao Peng, Zhifeng Hao, Lei Jiang, Kongjing Gu, Yanbing Liu, Philip S. Yu:
Dialogues Aspect-based Sentiment Quadruple Extraction via Structural Entropy Minimization Partitioning. CIKM 2025: 2326-2335 - [c1145]Yue Huang, Jingyu Tang, Dongping Chen, Bingda Tang, Yao Wan, Lichao Sun, Philip S. Yu, Xiangliang Zhang:
Jailbreaking LLMs Through Alignment Vulnerabilities in Out-of-Distribution Settings. CIKM 2025: 4817-4821 - [c1144]Zhichen Zeng, Xiaolong Liu, Mengyue Hang, Xiaoyi Liu, Qinghai Zhou, Chaofei Yang, Yiqun Liu, Yichen Ruan, Laming Chen, Yuxin Chen, Yujia Hao, Jiaqi Xu, Jade Nie, Xi Liu, Buyun Zhang, Wei Wen, Siyang Yuan, Hang Yin, Xin Zhang, Kai Wang, Wen-Yen Chen, Yiping Han, Huayu Li, Chunzhi Yang, Bo Long, Philip S. Yu, Hanghang Tong, Jiyan Yang:
InterFormer: Effective Heterogeneous Interaction Learning for Click-Through Rate Prediction. CIKM 2025: 6225-6233 - [c1143]Qingyun Sun, Ziwei Zhang, Xingcheng Fu, Yangqiu Song, Jianxin Li, Philip S. Yu:
Frontiers in Graph Machine Learning for the Large Model Era. CIKM 2025: 6927-6929 - [c1142]Yueqing Liang, Liangwei Yang, Chen Wang, Xiongxiao Xu, Philip S. Yu, Kai Shu:
Taxonomy-Guided Zero-Shot Recommendations with LLMs. COLING 2025: 1520-1530 - [c1141]Diandian Guo, Cong Cao, Fangfang Yuan, Yanbing Liu, Guangjie Zeng, Xiaoyan Yu, Hao Peng, Philip S. Yu:
Multi-View Incongruity Learning for Multimodal Sarcasm Detection. COLING 2025: 1754-1766 - [c1140]Alvin Chin, Justin Chan, Joshua Garcia, Aria Barve, Kevin Leicht, Philip S. Yu:
Improving Social Connections Through Mobile Social Networks. COMPSAC 2025: 1770-1775 - [c1139]Alvin Chin, Kevin Leicht, Philip S. Yu, Diego Gómez-Zará:
Ephemeral Social Networking: Connecting People from Offline to Online. HCI (61) 2025: 176-185 - [c1138]Lu Bai, Lixin Cui, Ming Li, Peng Ren, Yue Wang, Lichi Zhang, Philip S. Yu, Edwin R. Hancock:
AEGK: Aligned Entropic Graph Kernels Through Continuous-Time Quantum Walks: (Extended Abstract). ICDE 2025: 1-2 - [c1137]Xinqi Du, Ziyue Li, Cheng Long, Yongheng Xing, Philip S. Yu, Hechang Chen:
FELight: Fairness-Aware Traffic Signal Control via Sample-Efficient Reinforcement Learning (Extended Abstract). ICDE 2025: 4726-4727 - [c1136]Lu Bai, Lixin Cui, Yue Wang, Ming Li, Jing Li, Philip S. Yu, Edwin R. Hancock:
HAQJSK: Hierarchical-Aligned Quantum Jensen-Shannon Kernels for Graph Classification (Extended Abstract). ICDE 2025: 4738-4739 - [c1135]Fangxin Wang, Kay Liu, Sourav Medya, Philip S. Yu:
BANGS: Game-theoretic Node Selection for Graph Self-Training. ICLR 2025 - [c1134]Yinghui Li, Haojing Huang, Jiayi Kuang, Yangning Li, Shu-Yu Guo, Chao Qu, Xiaoyu Tan, Hai-Tao Zheng, Ying Shen, Philip S. Yu:
Refine Knowledge of Large Language Models via Adaptive Contrastive Learning. ICLR 2025 - [c1133]Yangning Li, Yinghui Li, Xinyu Wang, Yong Jiang, Zhen Zhang, Xinran Zheng, Hui Wang, Hai-Tao Zheng, Fei Huang, Jingren Zhou, Philip S. Yu:
Benchmarking Multimodal Retrieval Augmented Generation with Dynamic VQA Dataset and Self-adaptive Planning Agent. ICLR 2025 - [c1132]Aiwei Liu, Haoping Bai, Zhiyun Lu, Yanchao Sun, Xiang Kong, Xiaoming Simon Wang, Jiulong Shan, Albin Madappally Jose, Xiaojiang Liu, Lijie Wen, Philip S. Yu, Meng Cao:
TIS-DPO: Token-level Importance Sampling for Direct Preference Optimization With Estimated Weights. ICLR 2025 - [c1131]Aiwei Liu, Sheng Guan, Yiming Liu, Leyi Pan, Yifei Zhang, Liancheng Fang, Lijie Wen, Philip S. Yu, Xuming Hu:
Can Watermarked LLMs be Identified by Users via Crafted Prompts? ICLR 2025 - [c1130]Jiawen Qin, Haonan Yuan, Qingyun Sun, Lyujin Xu, Jiaqi Yuan, Pengfeng Huang, Zhaonan Wang, Xingcheng Fu, Hao Peng, Jianxin Li, Philip S. Yu:
IGL-Bench: Establishing the Comprehensive Benchmark for Imbalanced Graph Learning. ICLR 2025 - [c1129]Hengrui Zhang, Liancheng Fang, Qitian Wu, Philip S. Yu:
DiffPuter: Empowering Diffusion Models for Missing Data Imputation. ICLR 2025 - [c1128]Cheng Hu, Fangfang Yuan, Cong Cao, Pu Li, Guangjie Zeng, Yanbing Liu, Hao Peng, Philip S. Yu:
Counterfactual-Augmented Representation Learning based Event Prediction. ICME 2025: 1-6 - [c1127]Yinghui Li, Jiayi Kuang, Haojing Huang, Zhikun Xu, Xinnian Liang, Yi Yu, Wenlian Lu, Yangning Li, Xiaoyu Tan, Chao Qu, Ying Shen, Hai-Tao Zheng, Philip S. Yu:
One Example Shown, Many Concepts Known! Counterexample-Driven Conceptual Reasoning in Mathematical LLMs. ICML 2025 - [c1126]Haonan Yuan, Qingyun Sun, Junhua Shi, Xingcheng Fu, Bryan Hooi, Jianxin Li, Philip S. Yu:
How Much Can Transfer? BRIDGE: Bounded Multi-Domain Graph Foundation Model with Generalization Guarantees. ICML 2025 - [c1125]Hengrui Zhang, Liancheng Fang, Qitian Wu, Philip S. Yu:
TabNAT: A Continuous-Discrete Joint Generative Framework for Tabular Data. ICML 2025 - [c1124]Junyou Zhu, Langzhou He, Chao Gao, Dongpeng Hou, Zhen Su, Philip S. Yu, Jürgen Kurths, Frank Hellmann:
SDMG: Smoothing Your Diffusion Models for Powerful Graph Representation Learning. ICML 2025 - [c1123]Li Sun, Suyang Zhou, Bowen Fang, Hechuan Zhang, Junda Ye, Yutong Ye, Philip S. Yu:
Trace: Structural Riemannian Bridge Matching for Transferable Source Localization in Information Propagation. IJCAI 2025: 3308-3316 - [c1122]Kun Peng, Chaodong Tong, Cong Cao, Hao Peng, Qian Li, Guanlin Wu, Lei Jiang, Yanbing Liu, Philip S. Yu:
T-T: Table Transformer for Tagging-based Aspect Sentiment Triplet Extraction. IJCAI 2025: 8222-8230 - [c1121]Zhilin Zhao, Longbing Cao, Philip S. Yu:
Out-of-Distribution Detection by Regaining Lost Clues (Abstract Reprint). IJCAI 2025: 10961 - [c1120]Ya-Wen Teng, De-Nian Yang, Yishuo Shi, Guang-Siang Lee, Wang-Chien Lee, Philip S. Yu, Ming-Syan Chen:
Breeding-aware Revenue Maximization for NFT Viral Marketing on Social Networks. KDD (2) 2025: 2823-2834 - [c1119]Shu Pu, Yaochen Wang, Dongping Chen, Yuhang Chen, Guohao Wang, Qi Qin, Zhongyi Zhang, Zhiyuan Zhang, Zetong Zhou, Shuang Gong, Yi Gui, Yao Wan, Philip S. Yu:
Judge Anything: MLLM as a Judge Across Any Modality. KDD (2) 2025: 5742-5753 - [c1118]Liangbo Ning, Ziran Liang, Zhuohang Jiang, Haohao Qu, Yujuan Ding, Wenqi Fan, Xiaoyong Wei, Shanru Lin, Hui Liu, Philip S. Yu, Qing Li:
A Survey of WebAgents: Towards Next-Generation AI Agents for Web Automation with Large Foundation Models. KDD (2) 2025: 6140-6150 - [c1117]Yuxuan Liang, Yu Zheng, Chuishi Meng, Yanhua Li, Jieping Ye, Philip S. Yu, Ouri Wolfson:
The 14th International Workshop on Urban Computing. KDD (2) 2025: 6284-6285 - [c1116]Qingsong Wen, Yongfeng Zhang, Zhiwei Liu, Julian J. McAuley, Hua Wei, Linsey Pang, Wei Liu, Philip S. Yu:
The 4th Workshop on AI Agent for Information Retrieval: Generating and Ranking. KDD (2) 2025: 6298-6299 - [c1115]Leyi Pan, Aiwei Liu, Yijian Lu, Zitian Gao, Yichen Di, Lijie Wen, Irwin King, Philip S. Yu:
WaterSeeker: Pioneering Efficient Detection of Watermarked Segments in Large Documents. NAACL (Findings) 2025: 2866-2882 - [c1114]Hoang Nguyen, Khyati Mahajan, Vikas Yadav, Julian Salazar, Philip S. Yu, Masoud Hashemi, Rishabh Maheshwary:
Prompting with Phonemes: Enhancing LLMs' Multilinguality for Non-Latin Script Languages. NAACL (Long Papers) 2025: 11975-11994 - [c1113]Kay Liu, Jiahao Ding, MohamadAli Torkamani, Philip S. Yu:
TGTOD: A Global Temporal Graph Transformer for Outlier Detection at Scale. PAKDD (2) 2025: 251-263 - [c1112]Weizhi Zhang, Liangwei Yang, Zihe Song, Henry Peng Zou, Ke Xu, Yuanjie Zhu, Philip S. Yu:
SGCL: Unifying Self-Supervised and Supervised Learning for Graph Recommendation. RecSys 2025: 671-676 - [c1111]Minhui Xie, Hao Peng, Pu Li, Guangjie Zeng, Shuhai Wang, Jia Wu, Peng Li, Philip S. Yu:
Hierarchical Superpixel Segmentation via Structural Information Theory. SDM 2025: 242-251 - [c1110]Jiangshu Du, Wenpeng Yin, Philip S. Yu:
ScaleFormer: Span Representation Cumulation for Long-Context Transformer. SIGIR-AP 2025: 337-342 - [c1109]Feiran Huang, Yuanchen Bei, Zhenghang Yang, Junyi Jiang, Hao Chen, Qijie Shen, Senzhang Wang, Fakhri Karray, Philip S. Yu:
Large Language Model Simulator for Cold-Start Recommendation. WSDM 2025: 261-270 - [c1108]Yuwei Cao, Liangwei Yang, Zhiwei Liu, Yuqing Liu, Chen Wang, Yueqing Liang, Hao Peng, Philip S. Yu:
Graph-Sequential Alignment and Uniformity: Toward Enhanced Recommendation Systems. WWW (Companion Volume) 2025: 888-892 - [c1107]Li Sun, Zhenhao Huang, Suyang Zhou, Qiqi Wan, Hao Peng, Philip S. Yu:
RiemannGFM: Learning a Graph Foundation Model from Riemannian Geometry. WWW 2025: 1154-1165 - [c1106]Ke Xu, Weizhi Zhang, Zihe Song, Yuanjie Zhu, Philip S. Yu:
Graph Neural Controlled Differential Equations For Collaborative Filtering. WWW (Companion Volume) 2025: 1446-1449 - [c1105]Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu:
Training Large Recommendation Models via Graph-Language Tokens Alignment. WWW (Companion Volume) 2025: 1470-1474 - [c1104]Qingsong Wen, Yongfeng Zhang, Zhiwei Liu, Julian J. McAuley, Hua Wei, Linsey Pang, Wei Liu, Philip S. Yu:
The 3rd Workshop on AI Agent for Information Retrieval: Generating and Ranking. WWW (Companion Volume) 2025: 1659-1662 - [c1103]Di Jin, Cuiying Huo, Jiayi Shi, Dongxiao He, Jianguo Wei, Philip S. Yu:
LLGformer: Learnable Long-range Graph Transformer for Traffic Flow Prediction. WWW 2025: 2860-2871 - [c1102]Yantuan Xian, Pu Li, Hao Peng, Zhengtao Yu, Yan Xiang, Philip S. Yu:
Community Detection in Large-Scale Complex Networks via Structural Entropy Game. WWW 2025: 3930-3941 - [i646]Weizhi Zhang, Yuanchen Bei, Liangwei Yang, Henry Peng Zou, Peilin Zhou, Aiwei Liu, Yinghui Li, Hao Chen, Jianling Wang, Yu Wang, Feiran Huang, Sheng Zhou, Jiajun Bu, Allen Lin, James Caverlee, Fakhri Karray, Irwin King, Philip S. Yu:
Cold-Start Recommendation towards the Era of Large Language Models (LLMs): A Comprehensive Survey and Roadmap. CoRR abs/2501.01945 (2025) - [i645]Jiayang Wu, Wensheng Gan, Huashen Lu, Philip S. Yu:
Graph Contrastive Learning on Multi-label Classification for Recommendations. CoRR abs/2501.06985 (2025) - [i644]Minhui Xie, Hao Peng, Pu Li, Guangjie Zeng, Shuhai Wang, Jia Wu, Peng Li, Philip S. Yu:
Hierarchical Superpixel Segmentation via Structural Information Theory. CoRR abs/2501.07069 (2025) - [i643]Jiayang Wu, Wensheng Gan, Jiahao Zhang, Philip S. Yu:
ADKGD: Anomaly Detection in Knowledge Graphs with Dual-Channel Training. CoRR abs/2501.07078 (2025) - [i642]Jia-Hao Syu, Jerry Chun-Wei Lin, Philip S. Yu:
Distributed Multi-Head Learning Systems for Power Consumption Prediction. CoRR abs/2501.12133 (2025) - [i641]Ke Xu, Weizhi Zhang, Zihe Song, Yuanjie Zhu, Philip S. Yu:
Graph Neural Controlled Differential Equations For Collaborative Filtering. CoRR abs/2501.13908 (2025) - [i640]Yantuan Xian, Pu Li, Hao Peng, Zhengtao Yu, Yan Xiang, Philip S. Yu:
Community Detection in Large-Scale Complex Networks via Structural Entropy Game. CoRR abs/2501.15130 (2025) - [i639]Wensheng Gan, Zhenyao Ning, Zhenlian Qi, Philip S. Yu:
Mixture of Experts (MoE): A Big Data Perspective. CoRR abs/2501.16352 (2025) - [i638]Yibo Yan, Shen Wang, Jiahao Huo, Jingheng Ye, Zhendong Chu, Xuming Hu, Philip S. Yu, Carla P. Gomes, Bart Selman, Qingsong Wen:
Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning. CoRR abs/2502.02871 (2025) - [i637]Li Sun, Ziheng Zhang, Zixi Wang, Yujie Wang, Qiqi Wan, Hao Li, Hao Peng, Philip S. Yu:
Pioneer: Physics-informed Riemannian Graph ODE for Entropy-increasing Dynamics. CoRR abs/2502.03236 (2025) - [i636]Li Sun, Zhenhao Huang, Suyang Zhou, Qiqi Wan, Hao Peng, Philip S. Yu:
RiemannGFM: Learning a Graph Foundation Model from Riemannian Geometry. CoRR abs/2502.03251 (2025) - [i635]Jingheng Ye, Shen Wang, Deqing Zou, Yibo Yan, Kun Wang, Hai-Tao Zheng, Zenglin Xu, Irwin King, Philip S. Yu, Qingsong Wen:
Position: LLMs Can be Good Tutors in Foreign Language Education. CoRR abs/2502.05467 (2025) - [i634]Yibo Wang, Congying Xia, Wenting Zhao, Jiangshu Du, Chunyu Miao, Zhongfen Deng, Philip S. Yu, Chen Xing:
ProjectTest: A Project-level LLM Unit Test Generation Benchmark and Impact of Error Fixing Mechanisms. CoRR abs/2502.06556 (2025) - [i633]Yinghui Li, Haojing Huang, Jiayi Kuang, Yangning Li, Shu-Yu Guo, Chao Qu, Xiaoyu Tan, Hai-Tao Zheng, Ying Shen, Philip S. Yu:
Refine Knowledge of Large Language Models via Adaptive Contrastive Learning. CoRR abs/2502.07184 (2025) - [i632]Jiayang Wu, Wensheng Gan, Philip S. Yu:
Graph Diffusion Network for Drug-Gene Prediction. CoRR abs/2502.09335 (2025) - [i631]Yinghui Li, Jiayi Kuang, Haojing Huang, Zhikun Xu, Xinnian Liang, Yi Yu, Wenlian Lu, Yangning Li, Xiaoyu Tan, Chao Qu, Ying Shen, Hai-Tao Zheng, Philip S. Yu:
One Example Shown, Many Concepts Known! Counterexample-Driven Conceptual Reasoning in Mathematical LLMs. CoRR abs/2502.10454 (2025) - [i630]Leyi Pan, Aiwei Liu, Shiyu Huang, Yijian Lu, Xuming Hu, Lijie Wen, Irwin King, Philip S. Yu:
Can LLM Watermarks Robustly Prevent Unauthorized Knowledge Distillation? CoRR abs/2502.11598 (2025) - [i629]Yue Huang, Chujie Gao, Siyuan Wu, Haoran Wang, Xiangqi Wang, Yujun Zhou, Yanbo Wang, Jiayi Ye, Jiawen Shi, Qihui Zhang, Yuan Li, Han Bao, Zhaoyi Liu, Tianrui Guan, Dongping Chen, Ruoxi Chen, Kehan Guo, Andy Zou, Bryan Hooi Kuen-Yew, Caiming Xiong, Elias Stengel-Eskin, Hongyang Zhang, Hongzhi Yin, Huan Zhang, Huaxiu Yao, Jaehong Yoon, Jieyu Zhang, Kai Shu, Kaijie Zhu, Ranjay Krishna, Swabha Swayamdipta, Taiwei Shi, Weijia Shi, Xiang Li, Yiwei Li, Yuexing Hao, Zhihao Jia, Zhize Li, Xiuying Chen, Zhengzhong Tu, Xiyang Hu, Tianyi Zhou, Jieyu Zhao, Lichao Sun, Furong Huang, Or Cohen Sasson, Prasanna Sattigeri, Anka Reuel, Max Lamparth, Yue Zhao, Nouha Dziri, Yu Su, Huan Sun, Heng Ji, Chaowei Xiao, Mohit Bansal, Nitesh V. Chawla, Jian Pei, Jianfeng Gao, Michael Backes, Philip S. Yu, Neil Zhenqiang Gong, Pin-Yu Chen, Bo Li, Xiangliang Zhang:
On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective. CoRR abs/2502.14296 (2025) - [i628]Liancheng Fang, Aiwei Liu, Hengrui Zhang, Henry Peng Zou, Weizhi Zhang, Philip S. Yu:
TabGen-ICL: Residual-Aware In-Context Example Selection for Tabular Data Generation. CoRR abs/2502.16414 (2025) - [i627]Yaozu Wu, Dongyuan Li, Yankai Chen, Renhe Jiang, Henry Peng Zou, Liancheng Fang, Zhen Wang, Philip S. Yu:
Multi-Agent Autonomous Driving Systems with Large Language Models: A Survey of Recent Advances. CoRR abs/2502.16804 (2025) - [i626]Yujie Feng, Xujia Wang, Zexin Lu, Shenghong Fu, Guangyuan Shi, Yongxin Xu, Yasha Wang, Philip S. Yu, Xu Chu, Xiao-Ming Wu:
Recurrent Knowledge Identification and Fusion for Language Model Continual Learning. CoRR abs/2502.17510 (2025) - [i625]Xiongxiao Xu, Haoran Wang, Yueqing Liang, Philip S. Yu, Yue Zhao, Kai Shu:
Can Multimodal LLMs Perform Time Series Anomaly Detection? CoRR abs/2502.17812 (2025) - [i624]Zhijun Chen, Jingzheng Li, Pengpeng Chen, Zhuoran Li, Kai Sun, Yuankai Luo, Qianren Mao, Dingqi Yang, Hailong Sun, Philip S. Yu:
Harnessing Multiple Large Language Models: A Survey on LLM Ensemble. CoRR abs/2502.18036 (2025) - [i623]Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu:
Training Large Recommendation Models via Graph-Language Token Alignment. CoRR abs/2502.18757 (2025) - [i622]Henry Peng Zou, Zhengyao Gu, Yue Zhou, Yankai Chen, Weizhi Zhang, Liancheng Fang, Yibo Wang, Yangning Li, Kay Liu, Philip S. Yu:
TestNUC: Enhancing Test-Time Computing Approaches through Neighboring Unlabeled Data Consistency. CoRR abs/2502.19163 (2025) - [i621]Yujie Feng, Liming Zhan, Zexin Lu, Yongxin Xu, Xu Chu, Yasha Wang, Jiannong Cao, Philip S. Yu, Xiao-Ming Wu:
GeoEdit: Geometric Knowledge Editing for Large Language Models. CoRR abs/2502.19953 (2025) - [i620]Weizhi Zhang, Liangwei Yang, Wooseong Yang, Henry Peng Zou, Yuqing Liu, Ke Xu, Sourav Medya, Philip S. Yu:
LLMInit: A Free Lunch from Large Language Models for Selective Initialization of Recommendation. CoRR abs/2503.01814 (2025) - [i619]Zhengyao Gu, Henry Peng Zou, Yankai Chen, Aiwei Liu, Weizhi Zhang, Philip S. Yu:
Semi-Supervised In-Context Learning: A Baseline Study. CoRR abs/2503.03062 (2025) - [i618]Jifan Zhang, Fangxin Wang, Philip S. Yu, Kaize Ding, Shixiang Zhu:
Topology-Aware Conformal Prediction for Stream Networks. CoRR abs/2503.04981 (2025) - [i617]Guiyao Tie, Zeli Zhao, Dingjie Song, Fuyang Wei, Rong Zhou, Yurou Dai, Wen Yin, Zhejian Yang, Jiangyue Yan, Yao Su, Zhenhan Dai, Yifeng Xie, Yihan Cao, Lichao Sun, Pan Zhou, Lifang He, Hechang Chen, Yu Zhang, Qingsong Wen, Tianming Liu, Neil Zhenqiang Gong, Jiliang Tang, Caiming Xiong, Heng Ji, Philip S. Yu, Jianfeng Gao:
A Survey on Post-training of Large Language Models. CoRR abs/2503.06072 (2025) - [i616]Zhendong Chu, Shen Wang, Jian Xie, Tinghui Zhu, Yibo Yan, Jinheng Ye, Aoxiao Zhong, Xuming Hu, Jing Liang, Philip S. Yu, Qingsong Wen:
LLM Agents for Education: Advances and Applications. CoRR abs/2503.11733 (2025) - [i615]Yue Xing, Wensheng Gan, Qidi Chen, Philip S. Yu:
AI-Generated Content in Landscape Architecture: A Survey. CoRR abs/2503.16435 (2025) - [i614]Shu Pu, Yaochen Wang, Dongping Chen, Yuhang Chen, Guohao Wang, Qi Qin, Zhongyi Zhang, Zhiyuan Zhang, Zetong Zhou, Shuang Gong, Yi Gui, Yao Wan, Philip S. Yu:
Judge Anything: MLLM as a Judge Across Any Modality. CoRR abs/2503.17489 (2025) - [i613]Yibo Yan, Shen Wang, Jiahao Huo, Philip S. Yu, Xuming Hu, Qingsong Wen:
MathAgent: Leveraging a Mixture-of-Math-Agent Framework for Real-World Multimodal Mathematical Error Detection. CoRR abs/2503.18132 (2025) - [i612]Junyu Luo, Weizhi Zhang, Ye Yuan, Yusheng Zhao, Junwei Yang, Yiyang Gu, Bohan Wu, Binqi Chen, Ziyue Qiao, Qingqing Long, Rongcheng Tu, Xiao Luo, Wei Ju, Zhiping Xiao, Yifan Wang, Meng Xiao, Chenwu Liu, Jingyang Yuan, Shichang Zhang, Yiqiao Jin, Fan Zhang, Xian Wu, Hanqing Zhao, Dacheng Tao, Philip S. Yu, Ming Zhang:
Large Language Model Agent: A Survey on Methodology, Applications and Challenges. CoRR abs/2503.21460 (2025) - [i611]Liangbo Ning, Ziran Liang, Zhuohang Jiang, Haohao Qu, Yujuan Ding, Wenqi Fan, Xiaoyong Wei, Shanru Lin, Hui Liu, Philip S. Yu, Qing Li:
A Survey of WebAgents: Towards Next-Generation AI Agents for Web Automation with Large Foundation Models. CoRR abs/2503.23350 (2025) - [i610]Chen Wang, Mingdai Yang, Zhiwei Liu, Pan Li, Linsey Pang, Qingsong Wen, Philip S. Yu:
Automating Personalization: Prompt Optimization for Recommendation Reranking. CoRR abs/2504.03965 (2025) - [i609]Lixiang Xu, Xianwei Ding, Xin Yuan, Zhanlong Wang, Lu Bai, Enhong Chen, Philip S. Yu, Yuanyan Tang:
Improving Question Embeddings with Cognitiv Representation Optimization for Knowledge Tracing. CoRR abs/2504.04121 (2025) - [i608]Qingsong Lv, Yangning Li, Zihua Lan, Zishan Xu, Jiwei Tang, Yinghui Li, Wenhao Jiang, Hai-Tao Zheng, Philip S. Yu:
RAISE: Reinforenced Adaptive Instruction Selection For Large Language Models. CoRR abs/2504.07282 (2025) - [i607]Li Sun, Zhenhao Huang, Yujie Wang, Hongbo Lv, Chunyang Liu, Hao Peng, Philip S. Yu:
IsoSEL: Isometric Structural Entropy Learning for Deep Graph Clustering in Hyperbolic Space. CoRR abs/2504.09970 (2025) - [i606]Kun Wang, Guibin Zhang, Zhenhong Zhou, Jiahao Wu, Miao Yu, Shiqian Zhao, Chenlong Yin, Jinhu Fu, Yibo Yan, Hanjun Luo, Liang Lin, Zhihao Xu, Haolang Lu, Xinye Cao, Xinyun Zhou, Weifei Jin, Fanci Meng, Junyuan Mao, Hao Wu, Minghe Wang, Fan Zhang, Junfeng Fang, Chengwei Liu, Yifan Zhang, Qiankun Li, Chongye Guo, Yalan Qin, Yi Ding, Donghai Hong, Jiaming Ji, Xinfeng Li, Yifan Jiang, Dongxia Wang, Yihao Huang, Yufei Guo, Jen-tse Huang, Yanwei Yue, Wenke Huang, Guancheng Wan, Tianlin Li, Lei Bai, Jie Zhang, Qing Guo, Jingyi Wang, Tianlong Chen, Joey Tianyi Zhou, Xiaojun Jia, Weisong Sun, Cong Wu, Jing Chen, Xuming Hu, Yiming Li, Xiao Wang, Ningyu Zhang, Luu Anh Tuan, Guowen Xu, Tianwei Zhang, Xingjun Ma, Xiang Wang, Bo An, Jun Sun, Mohit Bansal, Shirui Pan, Yuval Elovici, Bhavya Kailkhura, Bo Li, Yaodong Yang, Hongwei Li, Wenyuan Xu, Yizhou Sun, Wei Wang, Qing Li, Ke Tang, Yu-Gang Jiang, Felix Juefei-Xu, Hui Xiong, Xiaofeng Wang, Shuicheng Yan, Dacheng Tao, Philip S. Yu, Qingsong Wen, Yang Liu:
A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment. CoRR abs/2504.15585 (2025) - [i605]Yusheng Zhao, Junyu Luo, Xiao Luo, Weizhi Zhang, Zhiping Xiao, Wei Ju, Philip S. Yu, Ming Zhang:
Multifaceted Evaluation of Audio-Visual Capability for MLLMs: Effectiveness, Efficiency, Generalizability and Robustness. CoRR abs/2504.16936 (2025) - [i604]Qianren Mao, Qili Zhang, Hanwen Hao, Zhentao Han, Runhua Xu, Weifeng Jiang, Qi Hu, Zhijun Chen, Tyler Zhou, Bo Li, Yangqiu Song, Jin Dong, Jianxin Li, Philip S. Yu:
Privacy-Preserving Federated Embedding Learning for Localized Retrieval-Augmented Generation. CoRR abs/2504.19101 (2025) - [i603]Shengli Sun, Peng Xu, Guanming Jiang, Philip S. Yu, Yi Li:
Effective Index Construction Algorithm for Optimal (k,η)-cores Computation. CoRR abs/2504.20795 (2025) - [i602]Haoyan Xu, Zhengtao Yao, Xuzhi Zhang, Ziyi Wang, Langzhou He, Yushun Dong, Philip S. Yu, Mengyuan Li, Yue Zhao:
GLIP-OOD: Zero-Shot Graph OOD Detection with Foundation Model. CoRR abs/2504.21186 (2025) - [i601]Henry Peng Zou, Wei-Chieh Huang, Yaozu Wu, Yankai Chen, Chunyu Miao, Hoang Nguyen, Yue Zhou, Weizhi Zhang, Liancheng Fang, Langzhou He, Yangning Li, Dongyuan Li, Renhe Jiang, Xue Liu, Philip S. Yu:
A Survey on Large Language Model based Human-Agent Systems. CoRR abs/2505.00753 (2025) - [i600]Hao Peng, Xiang Huang, Shuo Sun, Ruitong Zhang, Philip S. Yu:
Adaptive and Robust DBSCAN with Multi-agent Reinforcement Learning. CoRR abs/2505.04339 (2025) - [i599]Kun Peng, Chaodong Tong, Cong Cao, Hao Peng, Qian Li, Guanlin Wu, Lei Jiang, Yanbing Liu, Philip S. Yu:
T-T: Table Transformer for Tagging-based Aspect Sentiment Triplet Extraction. CoRR abs/2505.05271 (2025) - [i598]Jizhou Guo, Zhaomin Wu, Philip S. Yu:
Reward Inside the Model: A Lightweight Hidden-State Reward Model for LLM's Best-of-N sampling. CoRR abs/2505.12225 (2025) - [i597]Haochen Yuan, Minting Pan, Yunbo Wang, Siyu Gao, Philip S. Yu, Xiaokang Yang:
Your Offline Policy is Not Trustworthy: Bilevel Reinforcement Learning for Sequential Portfolio Optimization. CoRR abs/2505.12759 (2025) - [i596]Li Li, Peilin Cai, Ryan A. Rossi, Franck Dernoncourt, Branislav Kveton, Junda Wu, Tong Yu, Linxin Song, Tiankai Yang, Yuehan Qin, Nesreen K. Ahmed, Samyadeep Basu, Subhojyoti Mukherjee, Ruiyi Zhang, Zhengmian Hu, Bo Ni, Yuxiao Zhou, Zichao Wang, Yue Huang, Yu Wang, Xiangliang Zhang, Philip S. Yu, Xiyang Hu, Yue Zhao:
A Personalized Conversational Benchmark: Towards Simulating Personalized Conversations. CoRR abs/2505.14106 (2025) - [i595]Yusheng Zhao, Xiao Luo, Weizhi Zhang, Wei Ju, Zhiping Xiao, Philip S. Yu, Ming Zhang:
MARCO: Meta-Reflection with Cross-Referencing for Code Reasoning. CoRR abs/2505.17481 (2025) - [i594]Yusheng Zhao, Qixin Zhang, Xiao Luo, Weizhi Zhang, Zhiping Xiao, Wei Ju, Philip S. Yu, Ming Zhang:
Dynamic Text Bundling Supervision for Zero-Shot Inference on Text-Attributed Graphs. CoRR abs/2505.17599 (2025) - [i593]Wooseong Yang, Weizhi Zhang, Yuqing Liu, Yuwei Han, Yu Wang, Junhyun Lee, Philip S. Yu:
Cold-Start Recommendation with Knowledge-Guided Retrieval-Augmented Generation. CoRR abs/2505.20773 (2025) - [i592]Liancheng Fang, Aiwei Liu, Henry Peng Zou, Yankai Chen, Hengrui Zhang, Zhongfen Deng, Philip S. Yu:
MUSE: Model-Agnostic Tabular Watermarking via Multi-Sample Selection. CoRR abs/2505.24267 (2025) - [i591]Lixiang Xu, Xianwei Ding, Xin Yuan, Richang Hong, Feiping Nie, Enhong Chen, Philip S. Yu:
Dynamic Programming Techniques for Enhancing Cognitive Representation in Knowledge Tracing. CoRR abs/2506.02949 (2025) - [i590]Ziyi Zhou, Xiaoming Zhang, Litian Zhang, Yibo Zhang, Zhenyu Guan, Chaozhuo Li, Philip S. Yu:
Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection. CoRR abs/2506.04739 (2025) - [i589]Weizhi Zhang, Xinyang Zhang, Chenwei Zhang, Liangwei Yang, Jingbo Shang, Zhepei Wei, Henry Peng Zou, Zijie Huang, Zhengyang Wang, Yifan Gao, Xiaoman Pan, Lian Xiong, Jingguo Liu, Philip S. Yu, Xian Li:
PersonaAgent: When Large Language Model Agents Meet Personalization at Test Time. CoRR abs/2506.06254 (2025) - [i588]Henry Peng Zou, Wei-Chieh Huang, Yaozu Wu, Chunyu Miao, Dongyuan Li, Aiwei Liu, Yue Zhou, Yankai Chen, Weizhi Zhang, Yangning Li, Liancheng Fang, Renhe Jiang, Philip S. Yu:
A Call for Collaborative Intelligence: Why Human-Agent Systems Should Precede AI Autonomy. CoRR abs/2506.09420 (2025) - [i587]Longzhu He, Chaozhuo Li, Peng Tang, Lichao Sun, Sen Su, Philip S. Yu:
Devil's Hand: Data Poisoning Attacks to Locally Private Graph Learning Protocols. CoRR abs/2506.09803 (2025) - [i586]Songyang Liu, Chaozhuo Li, Jiameng Qiu, Xi Zhang, Feiran Huang, Litian Zhang, Yiming Hei, Philip S. Yu:
The Scales of Justitia: A Comprehensive Survey on Safety Evaluation of LLMs. CoRR abs/2506.11094 (2025) - [i585]Tzu-Ling Lin, Wei-Chih Chen, Teng-Fang Hsiao, Hou-I Liu, Ya-Hsin Yeh, Yu Kai Chan, Wen-Sheng Lien, Po-Yen Kuo, Philip S. Yu, Hong-Han Shuai:
Breaking the Reviewer: Assessing the Vulnerability of Large Language Models in Automated Peer Review Under Textual Adversarial Attacks. CoRR abs/2506.11113 (2025) - [i584]Yi Wang, Zhenghong Wang, Fan Zhang, Chengling Tang, Chaogui Kang, Di Zhu, Zhongfu Ma, Sijie Ruan, Weiyu Zhang, Yu Zheng, Philip S. Yu, Yu Liu:
A Gravity-informed Spatiotemporal Transformer for Human Activity Intensity Prediction. CoRR abs/2506.13678 (2025) - [i583]Yuanchen Bei, Weizhi Zhang, Siwen Wang, Weizhi Chen, Sheng Zhou, Hao Chen, Yong Li, Jiajun Bu, Shirui Pan, Yizhou Yu, Irwin King, Fakhri Karray, Philip S. Yu:
Graphs Meet AI Agents: Taxonomy, Progress, and Future Opportunities. CoRR abs/2506.18019 (2025) - [i582]Weizhi Zhang, Yangning Li, Yuanchen Bei, Junyu Luo, Guancheng Wan, Liangwei Yang, Chenxuan Xie, Yuyao Yang, Wei-Chieh Huang, Chunyu Miao, Henry Peng Zou, Xiao Luo, Yusheng Zhao, Yankai Chen, Chunkit Chan, Peilin Zhou, Xinyang Zhang, Chenwei Zhang, Jingbo Shang, Ming Zhang, Yangqiu Song, Irwin King, Philip S. Yu:
From Web Search towards Agentic Deep Research: Incentivizing Search with Reasoning Agents. CoRR abs/2506.18959 (2025) - [i581]Chaozhuo Li, Pengbo Wang, Chenxu Wang, Litian Zhang, Zheng Liu, Qiwei Ye, Yuanbo Xu, Feiran Huang, Xi Zhang, Philip S. Yu:
Loki's Dance of Illusions: A Comprehensive Survey of Hallucination in Large Language Models. CoRR abs/2507.02870 (2025) - [i580]Yangning Li, Weizhi Zhang, Yuyao Yang, Wei-Chieh Huang, Yaozu Wu, Junyu Luo, Yuanchen Bei, Henry Peng Zou, Xiao Luo, Yusheng Zhao, Chunkit Chan, Yankai Chen, Zhongfen Deng, Yinghui Li, Hai-Tao Zheng, Dongyuan Li, Renhe Jiang, Ming Zhang, Yangqiu Song, Philip S. Yu:
Towards Agentic RAG with Deep Reasoning: A Survey of RAG-Reasoning Systems in LLMs. CoRR abs/2507.09477 (2025) - [i579]Lingzhe Zhang, Tong Jia, Mengxi Jia, Yifan Wu, Aiwei Liu, Yong Yang, Zhonghai Wu, Xuming Hu, Philip S. Yu, Ying Li:
A Survey of AIOps in the Era of Large Language Models. CoRR abs/2507.12472 (2025) - [i578]Shuang Liang, Lili Chen, Wensheng Gan, Philip S. Yu, Shengjie Zhao:
Targeted Mining of Time-Interval Related Patterns. CoRR abs/2507.12668 (2025) - [i577]Wenting Zhu, Chaozhuo Li, Qingpo Yang, Xi Zhang, Philip S. Yu:
T3MAL: Test-Time Fast Adaptation for Robust Multi-Scale Information Diffusion Prediction. CoRR abs/2507.12880 (2025) - [i576]Weizhi Zhang, Liangwei Yang, Zihe Song, Henry Peng Zou, Ke Xu, Yuanjie Zhu, Philip S. Yu:
SGCL: Unifying Self-Supervised and Supervised Learning for Graph Recommendation. CoRR abs/2507.13336 (2025) - [i575]Qingyun Sun, Jiaqi Yuan, Shan He, Xiao Guan, Haonan Yuan, Xingcheng Fu, Jianxin Li, Philip S. Yu:
DyG-RAG: Dynamic Graph Retrieval-Augmented Generation with Event-Centric Reasoning. CoRR abs/2507.13396 (2025) - [i574]Zhenyu Pan, Yutong Zhang, Jianshu Zhang, Haoran Lu, Haozheng Luo, Yuwei Han, Philip S. Yu, Manling Li, Han Liu:
FairReason: Balancing Reasoning and Social Bias in MLLMs. CoRR abs/2507.23067 (2025) - [i573]Jialun Zheng, Jie Liu, Jiannong Cao, Xiao Wang, Hanchen Yang, Yankai Chen, Philip S. Yu:
DP-DGAD: A Generalist Dynamic Graph Anomaly Detector with Dynamic Prototypes. CoRR abs/2508.00664 (2025) - [i572]Hanchen Yang, Jiaqi Wang, Jiannong Cao, Wengen Li, Jialun Zheng, Yangning Li, Chunyu Miao, Jihong Guan, Shuigeng Zhou, Philip S. Yu:
OKG-LLM: Aligning Ocean Knowledge Graph with Observation Data via LLMs for Global Sea Surface Temperature Prediction. CoRR abs/2508.00933 (2025) - [i571]Zhenyu Pan, Yiting Zhang, Yutong Zhang, Jianshu Zhang, Haozheng Luo, Yuwei Han, Dennis Wu, Hong-Yu Chen, Philip S. Yu, Manling Li, Han Liu:
Evo-MARL: Co-Evolutionary Multi-Agent Reinforcement Learning for Internalized Safety. CoRR abs/2508.03864 (2025) - [i570]Kun Peng, Cong Cao, Hao Peng, Zhifeng Hao, Lei Jiang, Kongjing Gu, Yanbing Liu, Philip S. Yu:
Dialogues Aspect-based Sentiment Quadruple Extraction via Structural Entropy Minimization Partitioning. CoRR abs/2508.05023 (2025) - [i569]Lingzhe Zhang, Liancheng Fang, Chiming Duan, Minghua He, Leyi Pan, Pei Xiao, Shiyu Huang, Yunpeng Zhai, Xuming Hu, Philip S. Yu, Aiwei Liu:
A Survey on Parallel Text Generation: From Parallel Decoding to Diffusion Language Models. CoRR abs/2508.08712 (2025) - [i568]Kun Peng, Cong Cao, Hao Peng, Guanlin Wu, Zhifeng Hao, Lei Jiang, Yanbing Liu, Philip S. Yu:
Emotion Transfer with Enhanced Prototype for Unseen Emotion Recognition in Conversation. CoRR abs/2508.19533 (2025) - [i567]Leyi Pan, Sheng Guan, Zheyu Fu, Luyang Si, Zian Wang, Xuming Hu, Irwin King, Philip S. Yu, Aiwei Liu, Lijie Wen:
MarkDiffusion: An Open-Source Toolkit for Generative Watermarking of Latent Diffusion Models. CoRR abs/2509.10569 (2025) - [i566]Yangning Li, Tingwei Lu, Yinghui Li, Yankai Chen, Wei-Chieh Huang, Wenhao Jiang, Hui Wang, Hai-Tao Zheng, Philip S. Yu:
Teaching According to Talents! Instruction Tuning LLMs with Competence-Aware Curriculum Learning. CoRR abs/2509.13790 (2025) - [i565]Qingfeng Zhou, Wensheng Gan, Zhenlian Qi, Philip S. Yu:
Utility-based Privacy Preserving Data Mining. CoRR abs/2509.15755 (2025) - [i564]Zhiyu Kan, Wensheng Gan, Zhenlian Qi, Philip S. Yu:
Advances in Large Language Models for Medicine. CoRR abs/2509.18690 (2025) - [i563]Jie Yang, Yifan Hu, Kexin Zhang, Luyang Niu, Yushun Dong, Philip S. Yu, Kaize Ding:
Revisiting Multivariate Time Series Forecasting with Missing Values. CoRR abs/2509.23494 (2025) - [i562]Yaozu Wu, Jizhou Guo, Dongyuan Li, Henry Peng Zou, Wei-Chieh Huang, Yankai Chen, Zhen Wang, Weizhi Zhang, Yangning Li, Meng Zhang, Renhe Jiang, Philip S. Yu:
PSG-Agent: Personality-Aware Safety Guardrail for LLM-based Agents. CoRR abs/2509.23614 (2025) - [i561]Fanlong Zeng, Wensheng Gan, Philip S. Yu:
GraphIFE: Rethinking Graph Imbalance Node Classification via Invariant Learning. CoRR abs/2509.23616 (2025) - [i560]Fanlong Zeng, Wensheng Gan, Jiayang Wu, Philip S. Yu:
Pure Node Selection for Imbalanced Graph Node Classification. CoRR abs/2509.23662 (2025) - [i559]Langzhou He, Junyou Zhu, Fangxin Wang, Junhua Liu, Haoyan Xu, Yue Zhao, Philip S. Yu, Qitian Wu:
Can Molecular Foundation Models Know What They Don't Know? A Simple Remedy with Preference Optimization. CoRR abs/2509.25509 (2025) - [i558]Jiayi Kuang, Haojing Huang, Yinghui Li, Xinnian Liang, Zhikun Xu, Yangning Li, Xiaoyu Tan, Chao Qu, Meishan Zhang, Ying Shen, Philip S. Yu:
Atomic Thinking of LLMs: Decoupling and Exploring Mathematical Reasoning Abilities. CoRR abs/2509.25725 (2025) - [i557]Zhenyu Pan, Yiting Zhang, Zhuo Liu, Yolo Yunlong Tang, Zeliang Zhang, Haozheng Luo, Yuwei Han, Jianshu Zhang, Dennis Wu, Hong-Yu Chen, Haoran Lu, Haoyang Fang, Manling Li, Chenliang Xu, Philip S. Yu, Han Liu:
AdvEvo-MARL: Shaping Internalized Safety through Adversarial Co-Evolution in Multi-Agent Reinforcement Learning. CoRR abs/2510.01586 (2025) - [i556]Jie Yang, Kexin Zhang, Guibin Zhang, Philip S. Yu, Kaize Ding:
Glocal Information Bottleneck for Time Series Imputation. CoRR abs/2510.04910 (2025) - [i555]Mingdai Yang, Nurendra Choudhary, Jiangshu Du, Edward W. Huang, Philip S. Yu, Karthik Subbian, Danai Koutra:
AgentDR Dynamic Recommendation with Implicit Item-Item Relations via LLM-based Agents. CoRR abs/2510.05598 (2025) - [i554]Chunyu Miao, Henry Peng Zou, Yangning Li, Yankai Chen, Yibo Wang, Fangxin Wang, Yifan Li, Wooseong Yang, Bowei He, Xinni Zhang, Dianzhi Yu, Hanchen Yang, Hoang H. Nguyen, Yue Zhou, Jie Yang, Jizhou Guo, Wenzhe Fan, Chin-Yuan Yeh, Panpan Meng, Liancheng Fang, Jinhu Qi, Wei-Chieh Huang, Zhengyao Gu, Yuwei Han, Langzhou He, Yuyao Yang, Yinghui Li, Hai-Tao Zheng, Xue Liu, Irwin King, Philip S. Yu:
RECODE-H: A Benchmark for Research Code Development with Interactive Human Feedback. CoRR abs/2510.06186 (2025) - [i553]Michal Koren, Or Peretz, Tai Dinh, Philip S. Yu:
Reinforcement Learning from Probabilistic Forecasts for Safe Decision-Making via Conditional Value-at-Risk Planning. CoRR abs/2510.08226 (2025) - [i552]Jian Zhu, Zhidong Lin, Wensheng Gan, Ruichu Cai, Zhifeng Hao, Philip S. Yu:
Efficient Mining of Low-Utility Sequential Patterns. CoRR abs/2510.10243 (2025) - [i551]Wei-Chieh Huang, Henry Peng Zou, Yaozu Wu, Dongyuan Li, Yankai Chen, Weizhi Zhang, Yangning Li, Angelo Zangari, Jizhou Guo, Chunyu Miao, Liancheng Fang, Langzhou He, Renhe Jiang, Philip S. Yu:
DeepResearchGuard: Deep Research with Open-Domain Evaluation and Multi-Stage Guardrails for Safety. CoRR abs/2510.10994 (2025) - [i550]Yuhang Chen, Tianpeng Lv, Siyi Zhang, Yixiang Yin, Yao Wan, Philip S. Yu, Dongping Chen:
Paper2Web: Let's Make Your Paper Alive! CoRR abs/2510.15842 (2025) - [i549]Junyu Ren, Wensheng Gan, Guangyu Zhang, Wei Zhong, Philip S. Yu:
Global-focal Adaptation with Information Separation for Noise-robust Transfer Fault Diagnosis. CoRR abs/2510.16033 (2025) - [i548]Yingguang Yang, Xianghua Zeng, Qi Wu, Hao Peng, Yutong Xia, Hao Liu, Bin Chong, Philip S. Yu:
RoBCtrl: Attacking GNN-Based Social Bot Detectors via Reinforced Manipulation of Bots Control Interaction. CoRR abs/2510.16035 (2025) - [i547]Li Sun, Zhenhao Huang, Min Zhang, Philip S. Yu:
Deeper with Riemannian Geometry: Overcoming Oversmoothing and Oversquashing for Graph Foundation Models. CoRR abs/2510.17457 (2025) - [i546]Yankai Chen, Xinni Zhang, Yifei Zhang, Yangning Li, Henry Peng Zou, Chunyu Miao, Weizhi Zhang, Xue Liu, Philip S. Yu:
Embracing Trustworthy Brain-Agent Collaboration as Paradigm Extension for Intelligent Assistive Technologies. CoRR abs/2510.22095 (2025) - [i545]Jiayi Kuang, Yinghui Li, Xin Zhang, Yangning Li, Di Yin, Xing Sun, Ying Shen, Philip S. Yu:
Process-Level Trajectory Evaluation for Environment Configuration in Software Engineering Agents. CoRR abs/2510.25694 (2025) - [i544]Jiayi Luo, Qingyun Sun, Beining Yang, Haonan Yuan, Xingcheng Fu, Yanbiao Ma, Jianxin Li, Philip S. Yu:
Robust Graph Condensation via Classification Complexity Mitigation. CoRR abs/2510.26451 (2025) - [i543]Qingyun Sun, Jiayi Luo, Haonan Yuan, Xingcheng Fu, Hao Peng, Jianxin Li, Philip S. Yu:
Evolving Graph Learning for Out-of-Distribution Generalization in Non-stationary Environments. CoRR abs/2511.02354 (2025) - [i542]Haonan Yuan, Qingyun Sun, Junhua Shi, Xingcheng Fu, Bryan Hooi, Jianxin Li, Philip S. Yu:
GRAVER: Generative Graph Vocabularies for Robust Graph Foundation Models Fine-tuning. CoRR abs/2511.05592 (2025) - [i541]Bowei He, Bowen Gao, Yankai Chen, Yanyan Lan, Chen Ma, Philip S. Yu, Ya-Qin Zhang, Wei-Ying Ma:
S2Drug: Bridging Protein Sequence and 3D Structure in Contrastive Representation Learning for Virtual Screening. CoRR abs/2511.07006 (2025) - [i540]Jiangshu Du, Wenpeng Yin, Philip S. Yu:
ScaleFormer: Span Representation Cumulation for Long-Context Transformer. CoRR abs/2511.10029 (2025) - [i539]Yuanjie Zhu, Liangwei Yang, Ke Xu, Weizhi Zhang, Zihe Song, Jindong Wang, Philip S. Yu:
LLM-MemCluster: Empowering Large Language Models with Dynamic Memory for Text Clustering. CoRR abs/2511.15424 (2025) - [i538]Xingtao Zhao, Hao Peng, Dingli Su, Xianghua Zeng, Chunyang Liu, Jinzhi Liao, Philip S. Yu:
SeSE: A Structural Information-Guided Uncertainty Quantification Framework for Hallucination Detection in LLMs. CoRR abs/2511.16275 (2025) - [i537]Kay Liu, Yuwei Han, Haoyan Xu, Henry Peng Zou, Yue Zhao, Philip S. Yu:
TAGFN: A Text-Attributed Graph Dataset for Fake News Detection in the Age of LLMs. CoRR abs/2511.21624 (2025) - [i536]Guangjie Zeng, Hao Peng, Angsheng Li, Li Sun, Chunyang Liu, Shengze Li, Yicheng Pan, Philip S. Yu:
Hyperbolic Continuous Structural Entropy for Hierarchical Clustering. CoRR abs/2512.00524 (2025) - [i535]Yangning Li, Shaoshen Chen, Yinghui Li, Yankai Chen, Hai-Tao Zheng, Hui Wang, Wenhao Jiang, Philip S. Yu:
AdmTree: Compressing Lengthy Context with Adaptive Semantic Trees. CoRR abs/2512.04550 (2025) - [i534]Shanghao Li, Jinda Han, Yibo Wang, Yuanjie Zhu, Zihe Song, Langzhou He, Kenan Kamel A Alghythee, Philip S. Yu:
Detecting Hallucinations in Graph Retrieval-Augmented Generation via Attention Patterns and Semantic Alignment. CoRR abs/2512.09148 (2025) - [i533]Bobo Li, Xudong Han, Jiang Liu, Yuzhe Ding, Liqiang Jing, Zhaoqi Zhang, Jinheng Li, Xinya Du, Fei Li, Meishan Zhang, Min Zhang, Aixin Sun, Philip S. Yu, Hao Fei:
Event Extraction in Large Language Model. CoRR abs/2512.19537 (2025) - [i532]Huashen Lu, Wensheng Gan, Guoting Chen, Zhichao Huang, Philip S. Yu:
Graph Attention-based Adaptive Transfer Learning for Link Prediction. CoRR abs/2512.22252 (2025) - 2024
- [j586]Jinqi Lai, Wensheng Gan, Jiayang Wu, Zhenlian Qi, Philip S. Yu:
Large language models in law: A survey. AI Open 5: 181-196 (2024) - [j585]Heng Xu, Tianqing Zhu, Lefeng Zhang, Wanlei Zhou, Philip S. Yu:
Machine Unlearning: A Survey. ACM Comput. Surv. 56(1): 9:1-9:36 (2024) - [j584]Huiqiang Chen, Tianqing Zhu, Tao Zhang, Wanlei Zhou, Philip S. Yu:
Privacy and Fairness in Federated Learning: On the Perspective of Tradeoff. ACM Comput. Surv. 56(2): 39:1-39:37 (2024) - [j583]Yao Wan, Zhangqian Bi, Yang He, Jianguo Zhang, Hongyu Zhang, Yulei Sui, Guandong Xu, Hai Jin, Philip S. Yu:
Deep Learning for Code Intelligence: Survey, Benchmark and Toolkit. ACM Comput. Surv. 56(12): 309:1-309:41 (2024) - [j582]Xinqi Du, Hechang Chen, Yongheng Xing, Philip S. Yu, Lifang He:
A Contrastive-Enhanced Ensemble Framework for Efficient Multi-Agent Reinforcement Learning. Expert Syst. Appl. 245: 123158 (2024) - [j581]Yao Chen, Wensheng Gan, Gengsen Huang, Yongdong Wu, Philip S. Yu:
Privacy-preserving federated discovery of DNA motifs with differential privacy. Expert Syst. Appl. 249: 123799 (2024) - [j580]Liangqi Yuan, Ziran Wang, Lichao Sun, Philip S. Yu, Christopher G. Brinton:
Decentralized Federated Learning: A Survey and Perspective. IEEE Internet Things J. 11(21): 34617-34638 (2024) - [j579]Shicheng Wan, Hong Lin, Wensheng Gan, Jiahui Chen, Philip S. Yu:
Web3: The Next Internet Revolution. IEEE Internet Things J. 11(21): 34811-34825 (2024) - [j578]Yijie Gui, Wensheng Gan, Yongdong Wu, Philip S. Yu:
Privacy preserving rare itemset mining. Inf. Sci. 662: 120262 (2024) - [j577]Kay Liu, Yingtong Dou, Xueying Ding, Xiyang Hu, Ruitong Zhang, Hao Peng, Lichao Sun, Philip S. Yu:
PyGOD: A Python Library for Graph Outlier Detection. J. Mach. Learn. Res. 25: 141:1-141:9 (2024) - [j576]Zefeng Chen, Wensheng Gan, Gengsen Huang, Yanxin Zheng, Philip S. Yu:
Towards utility-driven contiguous sequential patterns in uncertain multi-sequences. Knowl. Based Syst. 284: 111314 (2024) - [j575]Han Chen, Yuhua Li, Philip S. Yu, Yixiong Zou, Ruixuan Li:
DCMSL: Dual influenced community strength-boosted multi-scale graph contrastive learning. Knowl. Based Syst. 304: 112472 (2024) - [j574]Hao Peng, Jia Wu, Jiaxu Cui, Philip S. Yu:
Introduction to the special issue on recent advances in graph learning: theory, algorithms, applications, and systems. Int. J. Mach. Learn. Cybern. 15(1): 1-2 (2024) - [j573]Li Sun, Junda Ye, Jiawei Zhang, Yong Yang, Mingsheng Liu, Feiyang Wang, Philip S. Yu:
Contrastive sequential interaction network learning on co-evolving Riemannian spaces. Int. J. Mach. Learn. Cybern. 15(4): 1397-1413 (2024) - [j572]Zhongyuan Jiang, Haibo Liu, Jing Li, Xinghua Li, Jianfeng Ma, Philip S. Yu:
Target link protection against link-prediction-based attacks via artificial bee colony algorithm based on random walk. Int. J. Mach. Learn. Cybern. 15(11): 4959-4971 (2024) - [j571]Guangsi Shi, Daokun Zhang, Ming Jin, Shirui Pan, Philip S. Yu:
Towards complex dynamic physics system simulation with graph neural ordinary equations. Neural Networks 176: 106341 (2024) - [j570]Qian Li, Jianxin Li, Jia Wu, Xutan Peng, Cheng Ji, Hao Peng, Lihong Wang, Philip S. Yu:
Triplet-aware graph neural networks for factorized multi-modal knowledge graph entity alignment. Neural Networks 179: 106479 (2024) - [j569]Lilin Zhang, Ning Yang, Yanchao Sun, Philip S. Yu:
Provable Unrestricted Adversarial Training Without Compromise With Generalizability. IEEE Trans. Pattern Anal. Mach. Intell. 46(12): 8302-8319 (2024) - [j568]Xinqi Du, Hechang Chen, Che Wang, Yongheng Xing, Jielong Yang, Philip S. Yu, Yi Chang, Lifang He:
Robust multi-agent reinforcement learning via Bayesian distributional value estimation. Pattern Recognit. 145: 109917 (2024) - [j567]Jiayang Wu, Wensheng Gan, Han-Chieh Chao, Philip S. Yu:
Geospatial Big Data: Survey and Challenges. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 17: 17007-17020 (2024) - [j566]Jiushun Ma, Yuxin Huang, Linqin Wang, Xiang Huang, Hao Peng, Zhengtao Yu, Philip S. Yu:
Augmenting Low-Resource Cross-Lingual Summarization with Progression-Grounded Training and Prompting. ACM Trans. Asian Low Resour. Lang. Inf. Process. 23(9): 129:1-129:22 (2024) - [j565]Xiang Huang, Hao Peng, Dongcheng Zou, Zhiwei Liu, Jianxin Li, Kay Liu, Jia Wu, Jianlin Su, Philip S. Yu:
CoSENT: Consistent Sentence Embedding via Similarity Ranking. IEEE ACM Trans. Audio Speech Lang. Process. 32: 2800-2813 (2024) - [j564]Ran Song, Xiang Huang, Hao Peng, Shengxiang Gao, Zhengtao Yu, Philip S. Yu:
WDEA: The Structure and Semantic Fusion With Wasserstein Distance for Low-Resource Language Entity Alignment. IEEE ACM Trans. Audio Speech Lang. Process. 32: 4511-4525 (2024) - [j563]Linqin Wang, Xiang Huang, Zhengtao Yu, Hao Peng, Shengxiang Gao, Cunli Mao, Yuxin Huang, Ling Dong, Philip S. Yu:
Zero-Shot Text Normalization via Cross-Lingual Knowledge Distillation. IEEE ACM Trans. Audio Speech Lang. Process. 32: 4631-4646 (2024) - [j562]Senzhang Wang, Changdong Wang, Di Jin, Shirui Pan, Philip S. Yu:
Guest Editorial TBD Special Issue on Graph Machine Learning for Recommender Systems. IEEE Trans. Big Data 10(6): 682 (2024) - [j561]Qihua Feng, Peiya Li, Zhixun Lu, Chaozhuo Li, Zefan Wang, Zhiquan Liu, Chunhui Duan, Feiran Huang, Jian Weng, Philip S. Yu:
EViT: Privacy-Preserving Image Retrieval via Encrypted Vision Transformer in Cloud Computing. IEEE Trans. Circuits Syst. Video Technol. 34(8): 7467-7483 (2024) - [j560]Zhixiao Wang, Yahui Chai, Chengcheng Sun, Xiaobin Rui, Hao Mi, Xinyu Zhang, Philip S. Yu:
A Weighted Symmetric Graph Embedding Approach for Link Prediction in Undirected Graphs. IEEE Trans. Cybern. 54(2): 1037-1047 (2024) - [j559]Bin Pu, Jiansong Liu, Yan Kang, Jianguo Chen, Philip S. Yu:
MVSTT: A Multiview Spatial-Temporal Transformer Network for Traffic-Flow Forecasting. IEEE Trans. Cybern. 54(3): 1582-1595 (2024) - [j558]Jia Wu, Jian Yang, Philip S. Yu, Carlo Condo:
Special Section on Community Detection in Time-Varying Information and Computing Networks: Theory, Models, and Applications. IEEE Trans. Emerg. Top. Comput. 12(2): 402 (2024) - [j557]Yupeng Chang, Xu Wang, Jindong Wang, Yuan Wu, Linyi Yang, Kaijie Zhu, Hao Chen, Xiaoyuan Yi, Cunxiang Wang, Yidong Wang, Wei Ye, Yue Zhang, Yi Chang, Philip S. Yu, Qiang Yang, Xing Xie:
A Survey on Evaluation of Large Language Models. ACM Trans. Intell. Syst. Technol. 15(3): 39:1-39:45 (2024) - [j556]Chunkai Zhang, Yuting Yang, Zilin Du, Wensheng Gan, Philip S. Yu:
HUSP-SP: Faster Utility Mining on Sequence Data. ACM Trans. Knowl. Discov. Data 18(1): 5:1-5:21 (2024) - [j555]Chunkai Zhang, Maohua Lyu, Wensheng Gan, Philip S. Yu:
Totally-ordered Sequential Rules for Utility Maximization. ACM Trans. Knowl. Discov. Data 18(4): 80:1-80:23 (2024) - [j554]Gengsen Huang, Wensheng Gan, Philip S. Yu:
TaSPM: Targeted Sequential Pattern Mining. ACM Trans. Knowl. Discov. Data 18(5): 114:1-114:18 (2024) - [j553]Ting-Ting Su, Chang-Dong Wang, Wudong Xi, Jian-Huang Lai, Philip S. Yu:
Hierarchical Alignment With Polar Contrastive Learning for Next-Basket Recommendation. IEEE Trans. Knowl. Data Eng. 36(1): 199-210 (2024) - [j552]Chuanpan Zheng, Xiaoliang Fan, Shirui Pan, Haibing Jin, Zhaopeng Peng, Zonghan Wu, Cheng Wang, Philip S. Yu:
Spatio-Temporal Joint Graph Convolutional Networks for Traffic Forecasting. IEEE Trans. Knowl. Data Eng. 36(1): 372-385 (2024) - [j551]Yue Wang, Yao Wan, Lu Bai, Lixin Cui, Zhuo Xu, Ming Li, Philip S. Yu, Edwin R. Hancock:
Collaborative Knowledge Graph Fusion by Exploiting the Open Corpus. IEEE Trans. Knowl. Data Eng. 36(2): 475-489 (2024) - [j550]Wen-Zhi Li, Chang-Dong Wang, Jian-Huang Lai, Philip S. Yu:
Towards Effective and Robust Graph Contrastive Learning With Graph Autoencoding. IEEE Trans. Knowl. Data Eng. 36(2): 868-881 (2024) - [j549]Siyuan Guo, Lixin Zou, Hechang Chen, Bohao Qu, Haotian Chi, Philip S. Yu, Yi Chang:
Sample Efficient Offline-to-Online Reinforcement Learning. IEEE Trans. Knowl. Data Eng. 36(3): 1299-1310 (2024) - [j548]Xuming Hu, Zhaochen Hong, Chenwei Zhang, Aiwei Liu, Shiao Meng, Lijie Wen, Irwin King, Philip S. Yu:
Reading Broadly to Open Your Mind: Improving Open Relation Extraction With Search Documents Under Self-Supervisions. IEEE Trans. Knowl. Data Eng. 36(5): 2026-2040 (2024) - [j547]Shuaiqi Liu, Jiannong Cao, Zhongfen Deng, Wenting Zhao, Ruosong Yang, Zhiyuan Wen, Philip S. Yu:
Neural Abstractive Summarization for Long Text and Multiple Tables. IEEE Trans. Knowl. Data Eng. 36(6): 2572-2586 (2024) - [j546]Jiaqian Ren, Hao Peng, Lei Jiang, Zhiwei Liu, Jia Wu, Zhengtao Yu, Philip S. Yu:
Uncertainty-Guided Boundary Learning for Imbalanced Social Event Detection. IEEE Trans. Knowl. Data Eng. 36(6): 2701-2715 (2024) - [j545]Jiangnan Xia, Yu Yang, Senzhang Wang, Hongzhi Yin, Jiannong Cao, Philip S. Yu:
Bayes-Enhanced Multi-View Attention Networks for Robust POI Recommendation. IEEE Trans. Knowl. Data Eng. 36(7): 2895-2909 (2024) - [j544]Xinqi Du, Ziyue Li, Cheng Long, Yongheng Xing, Philip S. Yu, Hechang Chen:
FELight: Fairness-Aware Traffic Signal Control via Sample-Efficient Reinforcement Learning. IEEE Trans. Knowl. Data Eng. 36(9): 4678-4692 (2024) - [j543]Man-Sheng Chen, Chang-Dong Wang, Dong Huang, Jian-Huang Lai, Philip S. Yu:
Concept Factorization Based Multiview Clustering for Large-Scale Data. IEEE Trans. Knowl. Data Eng. 36(11): 5784-5796 (2024) - [j542]Haibo Wang, Chuan Zhou, Xin Chen, Jia Wu, Shirui Pan, Zhao Li, Jilong Wang, Philip S. Yu:
Graph Structure Reshaping Against Adversarial Attacks on Graph Neural Networks. IEEE Trans. Knowl. Data Eng. 36(11): 6344-6357 (2024) - [j541]Lu Bai, Lixin Cui, Yue Wang, Ming Li, Jing Li, Philip S. Yu, Edwin R. Hancock:
HAQJSK: Hierarchical-Aligned Quantum Jensen-Shannon Kernels for Graph Classification. IEEE Trans. Knowl. Data Eng. 36(11): 6370-6384 (2024) - [j540]Yi Zhang, Yuying Zhao, Zhaoqing Li, Xueqi Cheng, Yu Wang, Olivera Kotevska, Philip S. Yu, Tyler Derr:
A Survey on Privacy in Graph Neural Networks: Attacks, Preservation, and Applications. IEEE Trans. Knowl. Data Eng. 36(12): 7497-7515 (2024) - [j539]Zhangtao Cheng, Fan Zhou, Xovee Xu, Kunpeng Zhang, Goce Trajcevski, Ting Zhong, Philip S. Yu:
Information Cascade Popularity Prediction via Probabilistic Diffusion. IEEE Trans. Knowl. Data Eng. 36(12): 8541-8555 (2024) - [j538]Tengfei Ma, Yujie Chen, Wen Tao, Dashun Zheng, Xuan Lin, Patrick Cheong-Iao Pang, Yiping Liu, Yijun Wang, Longyue Wang, Bosheng Song, Xiangxiang Zeng, Philip S. Yu:
Learning to Denoise Biomedical Knowledge Graph for Robust Molecular Interaction Prediction. IEEE Trans. Knowl. Data Eng. 36(12): 8682-8694 (2024) - [j537]Fangxin Wang, Yuqing Liu, Kay Liu, Yibo Wang, Sourav Medya, Philip S. Yu:
Uncertainty in Graph Neural Networks: A Survey. Trans. Mach. Learn. Res. 2024 (2024) - [j536]Youwei Liang, Dong Huang, Chang-Dong Wang, Philip S. Yu:
Multi-View Graph Learning by Joint Modeling of Consistency and Inconsistency. IEEE Trans. Neural Networks Learn. Syst. 35(2): 2848-2862 (2024) - [j535]Xing Su, Shan Xue, Fanzhen Liu, Jia Wu, Jian Yang, Chuan Zhou, Wenbin Hu, Cécile Paris, Surya Nepal, Di Jin, Quan Z. Sheng, Philip S. Yu:
A Comprehensive Survey on Community Detection With Deep Learning. IEEE Trans. Neural Networks Learn. Syst. 35(4): 4682-4702 (2024) - [j534]Qian Li, Jianxin Li, Jiawei Sheng, Shiyao Cui, Jia Wu, Yiming Hei, Hao Peng, Shu Guo, Lihong Wang, Amin Beheshti, Philip S. Yu:
A Survey on Deep Learning Event Extraction: Approaches and Applications. IEEE Trans. Neural Networks Learn. Syst. 35(5): 6301-6321 (2024) - [j533]Lingjuan Lyu, Han Yu, Xingjun Ma, Chen Chen, Lichao Sun, Jun Zhao, Qiang Yang, Philip S. Yu:
Privacy and Robustness in Federated Learning: Attacks and Defenses. IEEE Trans. Neural Networks Learn. Syst. 35(7): 8726-8746 (2024) - [j532]Xunxun Wu, Chang-Dong Wang, Jia-Qi Lin, Wudong Xi, Philip S. Yu:
Motif-Based Contrastive Learning for Community Detection. IEEE Trans. Neural Networks Learn. Syst. 35(9): 11706-11719 (2024) - [j531]Jie Xu, Chaozhuo Li, Feiran Huang, Zhoujun Li, Xing Xie, Philip S. Yu:
Sinkhorn Distance Minimization for Adaptive Semi-Supervised Social Network Alignment. IEEE Trans. Neural Networks Learn. Syst. 35(10): 13340-13353 (2024) - [j530]Hao Peng, Jingyun Zhang, Xiang Huang, Zhifeng Hao, Angsheng Li, Zhengtao Yu, Philip S. Yu:
Unsupervised Social Bot Detection via Structural Information Theory. ACM Trans. Inf. Syst. 42(6): 148:1-148:42 (2024) - [j529]Hao Peng, Jian Yang, Jia Wu, Philip S. Yu:
Introduction to the Special Issue on Advanced Graph Mining on the Web: Theory, Algorithms, and Applications: Part 2. ACM Trans. Web 18(2): 16:1-16:2 (2024) - [c1101]Xiaorui Su, Pengwei Hu, Zhu-Hong You, Philip S. Yu, Lun Hu:
Dual-Channel Learning Framework for Drug-Drug Interaction Prediction via Relation-Aware Heterogeneous Graph Transformer. AAAI 2024: 249-256 - [c1100]Yuwei Cao, Hao Peng, Zhengtao Yu, Philip S. Yu:
Hierarchical and Incremental Structural Entropy Minimization for Unsupervised Social Event Detection. AAAI 2024: 8255-8264 - [c1099]Li Sun, Zhenhao Huang, Zixi Wang, Feiyang Wang, Hao Peng, Philip S. Yu:
Motif-Aware Riemannian Graph Neural Network with Generative-Contrastive Learning. AAAI 2024: 9044-9052 - [c1098]Jingyu Pu, Chenhang Cui, Xinyue Chen, Yazhou Ren, Xiaorong Pu, Zhifeng Hao, Philip S. Yu, Lifang He:
Adaptive Feature Imputation with Latent Graph for Deep Incomplete Multi-View Clustering. AAAI 2024: 14633-14641 - [c1097]Xuming Hu, Zhaochen Hong, Yong Jiang, Zhichao Lin, Xiaobin Wang, Pengjun Xie, Philip S. Yu:
Three Heads Are Better than One: Improving Cross-Domain NER with Progressive Decomposed Network. AAAI 2024: 18261-18269 - [c1096]Henry Peng Zou, Vinay Samuel, Yue Zhou, Weizhi Zhang, Liancheng Fang, Zihe Song, Philip S. Yu, Cornelia Caragea:
ImplicitAVE: An Open-Source Dataset and Multimodal LLMs Benchmark for Implicit Attribute Value Extraction. ACL (Findings) 2024: 338-354 - [c1095]Tao Zhang, Chenwei Zhang, Xian Li, Jingbo Shang, Hoang Nguyen, Philip S. Yu:
Stronger, Lighter, Better: Towards Life-Long Attribute Value Extraction for E-Commerce Products. ACL (Findings) 2024: 8631-8643 - [c1094]Xuming Hu, Xiaochuan Li, Junzhe Chen, Yinghui Li, Yangning Li, Xiaoguang Li, Yasheng Wang, Qun Liu, Lijie Wen, Philip S. Yu, Zhijiang Guo:
Evaluating Robustness of Generative Search Engine on Adversarial Factoid Questions. ACL (Findings) 2024: 10650-10671 - [c1093]Jiayang Wu, Wensheng Gan, Jinqi Lai, Guoting Chen, Philip S. Yu:
Drug-gene Associations with Graph Learning. BCB 2024: 61:1-61:6 - [c1092]Xuan Lin, Xi Zhang, Zu-Guo Yu, Yahui Long, Xiangxiang Zeng, Philip S. Yu:
CSCL-DTI: predicting drug-target interaction through cross-view and self-supervised contrastive learning. BIBM 2024: 707-712 - [c1091]Liangwei Yang, Zhiwei Liu, Jianguo Zhang, Rithesh Murthy, Shelby Heinecke, Huan Wang, Caiming Xiong, Philip S. Yu:
Personalized Multi-task Training for Recommender System. IEEE Big Data 2024: 413-422 - [c1090]Yuqing Liu, Yu Wang, Yuwei Cao, Lichao Sun, Philip S. Yu:
Visual Summary Thought of Large Vision-Language Models for Multimodal Recommendation. IEEE Big Data 2024: 456-461 - [c1089]Zehao Gu, Shiyang Zhou, Yun Xiong, Yang Luo, Hongrun Ren, Qiang Wang, Xiaofeng Gao, Philip S. Yu:
MSTEM: Masked Spatiotemporal Event Series Modeling for Urban Undisciplined Events Forecasting. CIKM 2024: 685-694 - [c1088]Chen Wang, Liangwei Yang, Zhiwei Liu, Xiaolong Liu, Mingdai Yang, Yueqing Liang, Philip S. Yu:
Collaborative Alignment for Recommendation. CIKM 2024: 2315-2325 - [c1087]Xiaoyan Yu, Yifan Wei, Pu Li, Shuaishuai Zhou, Hao Peng, Li Sun, Liehuang Zhu, Philip S. Yu:
DAMe: Personalized Federated Social Event Detection with Dual Aggregation Mechanism. CIKM 2024: 3052-3062 - [c1086]Hengrui Zhang, Shen Wang, Vassilis N. Ioannidis, Soji Adeshina, Jiani Zhang, Xiao Qin, Christos Faloutsos, Da Zheng, George Karypis, Philip S. Yu:
Revisit Orthogonality in Graph-Regularized MLPs. CIKM 2024: 3145-3154 - [c1085]Hengrui Zhang, Qitian Wu, Chenxiao Yang, Philip S. Yu:
InfoMLP: Unlocking the Potential of MLPs for Semi-Supervised Learning with Structured Data. CIKM 2024: 3155-3164 - [c1084]Weizhi Zhang, Liangwei Yang, Zihe Song, Henry Peng Zou, Ke Xu, Liancheng Fang, Philip S. Yu:
Do We Really Need Graph Convolution During Training? Light Post-Training Graph-ODE for Efficient Recommendation. CIKM 2024: 3248-3258 - [c1083]Luyi Ma, Xiaohan Li, Kamilia Ahmadi, Jianpeng Xu, Philip S. Yu, George Karypis:
3rd International Workshop on Industrial Recommendation Systems (IRS). CIKM 2024: 5588-5591 - [c1082]Yongfeng Zhang, Zhiwei Liu, Qingsong Wen, Linsey Pang, Wei Liu, Philip S. Yu:
AI Agent for Information Retrieval: Generating and Ranking. CIKM 2024: 5605-5607 - [c1081]Hoang Nguyen, Chenwei Zhang, Ye Liu, Natalie Parde, Eugene Rohrbaugh, Philip S. Yu:
CORI: CJKV Benchmark with Romanization Integration - a Step towards Cross-lingual Transfer beyond Textual Scripts. LREC/COLING 2024: 4008-4020 - [c1080]Yucheng Jin, Yun Xiong, Juncheng Fang, Xixi Wu, Dongxiao He, Xing Jia, Bingchen Zhao, Philip S. Yu:
Beyond the Known: Novel Class Discovery for Open-World Graph Learning. DASFAA (6) 2024: 117-133 - [c1079]Yibo Wang, Xiangjue Dong, James Caverlee, Philip S. Yu:
DA³: A Distribution-Aware Adversarial Attack against Language Models. EMNLP 2024: 1808-1825 - [c1078]Jiangshu Du, Yibo Wang, Wenting Zhao, Zhongfen Deng, Shuaiqi Liu, Renze Lou, Henry Peng Zou, Pranav Narayanan Venkit, Nan Zhang, Mukund Srinath, Haoran Zhang, Vipul Gupta, Yinghui Li, Tao Li, Fei Wang, Qin Liu, Tianlin Liu, Pengzhi Gao, Congying Xia, Chen Xing, Cheng Jiayang, Zhaowei Wang, Ying Su, Raj Sanjay Shah, Ruohao Guo, Jing Gu, Haoran Li, Kangda Wei, Zihao Wang, Lu Cheng, Surangika Ranathunga, Meng Fang, Jie Fu, Fei Liu, Ruihong Huang, Eduardo Blanco, Yixin Cao, Rui Zhang, Philip S. Yu, Wenpeng Yin:
LLMs Assist NLP Researchers: Critique Paper (Meta-)Reviewing. EMNLP 2024: 5081-5099 - [c1077]Xuming Hu, Junzhe Chen, Xiaochuan Li, Yufei Guo, Lijie Wen, Philip S. Yu, Zhijiang Guo:
Towards Understanding Factual Knowledge of Large Language Models. ICLR 2024 - [c1076]Aiwei Liu, Leyi Pan, Xuming Hu, Shuang Li, Lijie Wen, Irwin King, Philip S. Yu:
An Unforgeable Publicly Verifiable Watermark for Large Language Models. ICLR 2024 - [c1075]Li Sun, Zhenhao Huang, Hao Peng, Yujie Wang, Chunyang Liu, Philip S. Yu:
LSEnet: Lorentz Structural Entropy Neural Network for Deep Graph Clustering. ICML 2024 - [c1074]Yue Huang, Lichao Sun, Haoran Wang, Siyuan Wu, Qihui Zhang, Yuan Li, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Hanchi Sun, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bertie Vidgen, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, Joaquin Vanschoren, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yong Chen, Yue Zhao:
Position: TrustLLM: Trustworthiness in Large Language Models. ICML 2024 - [c1073]Fariba Lotfi, Amin Beheshti, Mansour Jamzad, Hamid Beigy, Jia Wu, Philip S. Yu:
The Open Story Model (OSM): Transforming Big Data into Interactive Narratives. ICWS 2024: 1177-1187 - [c1072]Xuexiong Luo, Jia Wu, Jian Yang, Shan Xue, Amin Beheshti, Quan Z. Sheng, David McAlpine, Paul F. Sowman, Alexis Giral, Philip S. Yu:
Graph Neural Networks for Brain Graph Learning: A Survey. IJCAI 2024: 8170-8178 - [c1071]Zhongyi Pei, Zhiyao Cen, Yipeng Huang, Chen Wang, Lin Liu, Philip S. Yu, Mingsheng Long, Jianmin Wang:
BTTackler: A Diagnosis-based Framework for Efficient Deep Learning Hyperparameter Optimization. KDD 2024: 2340-2351 - [c1070]Chen Wang, Ziwei Fan, Liangwei Yang, Mingdai Yang, Xiaolong Liu, Zhiwei Liu, Philip S. Yu:
Pre-Training with Transferable Attention for Addressing Market Shifts in Cross-Market Sequential Recommendation. KDD 2024: 2970-2979 - [c1069]Ronghui Xu, Hao Miao, Senzhang Wang, Philip S. Yu, Jianxin Wang:
PeFAD: A Parameter-Efficient Federated Framework for Time Series Anomaly Detection. KDD 2024: 3621-3632 - [c1068]Yuxuan Liang, Chuishi Meng, Yanhua Li, Yu Zheng, Jieping Ye, Qiang Yang, Philip S. Yu, Ouri Wolfson:
The 13th International Workshop on Urban Computing. KDD 2024: 6727-6728 - [c1067]Kay Liu, Hengrui Zhang, Ziqing Hu, Fangxin Wang, Philip S. Yu:
Data Augmentation for Supervised Graph Outlier Detection via Latent Diffusion Models. LoG 2024: 43 - [c1066]Wenting Zhao, Ye Liu, Tong Niu, Yao Wan, Philip S. Yu, Shafiq Joty, Yingbo Zhou, Semih Yavuz:
DIVKNOWQA: Assessing the Reasoning Ability of LLMs via Open-Domain Question Answering over Knowledge Base and Text. NAACL-HLT (Findings) 2024: 51-68 - [c1065]Wenting Zhao, Ye Liu, Yao Wan, Yibo Wang, Qingyang Wu, Zhongfen Deng, Jiangshu Du, Shuaiqi Liu, Yunlong Xu, Philip S. Yu:
kNN-ICL: Compositional Task-Oriented Parsing Generalization with Nearest Neighbor In-Context Learning. NAACL-HLT 2024: 326-337 - [c1064]Yinghui Li, Qingyu Zhou, Yuanzhen Luo, Shirong Ma, Yangning Li, Hai-Tao Zheng, Xuming Hu, Philip S. Yu:
When LLMs Meet Cunning Texts: A Fallacy Understanding Benchmark for Large Language Models. NeurIPS 2024 - [c1063]Qingyun Sun, Ziying Chen, Beining Yang, Cheng Ji, Xingcheng Fu, Sheng Zhou, Hao Peng, Jianxin Li, Philip S. Yu:
GC-Bench: An Open and Unified Benchmark for Graph Condensation. NeurIPS 2024 - [c1062]Li Sun, Zhenhao Huang, Qiqi Wan, Hao Peng, Philip S. Yu:
Spiking Graph Neural Network on Riemannian Manifolds. NeurIPS 2024 - [c1061]Yu Wang, Zhiwei Liu, Liangwei Yang, Philip S. Yu:
Conditional Denoising Diffusion for Sequential Recommendation. PAKDD (5) 2024: 156-169 - [c1060]Kun Peng, Lei Jiang, Hao Peng, Rui Liu, Zhengtao Yu, Jiaqian Ren, Zhifeng Hao, Philip S. Yu:
Prompt Based Tri-Channel Graph Convolution Neural Network for Aspect Sentiment Triplet Extraction. SDM 2024: 145-153 - [c1059]Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu:
Instruction-based Hypergraph Pretraining. SIGIR 2024: 501-511 - [c1058]Yuwei Cao, Hao Peng, Angsheng Li, Chenyu You, Zhifeng Hao, Philip S. Yu:
Multi-Relational Structural Entropy. UAI 2024: 532-546 - [c1057]Xiaolong Liu, Liangwei Yang, Zhiwei Liu, Mingdai Yang, Chen Wang, Hao Peng, Philip S. Yu:
Knowledge Graph Context-Enhanced Diversified Recommendation. WSDM 2024: 462-471 - [c1056]Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu:
Unified Pretraining for Recommendation via Task Hypergraphs. WSDM 2024: 891-900 - [c1055]Xusheng Zhao, Hao Peng, Qiong Dai, Xu Bai, Huailiang Peng, Yanbing Liu, Qinglang Guo, Philip S. Yu:
RDGCN: Reinforced Dependency Graph Convolutional Network for Aspect-based Sentiment Analysis. WSDM 2024: 976-984 - [c1054]Yue Huang, Kai Shu, Philip S. Yu, Lichao Sun:
From Creation to Clarification: ChatGPT's Journey Through the Fake News Quagmire. WWW (Companion Volume) 2024: 513-516 - [c1053]Chuan Shi, Cheng Yang, Yuan Fang, Lichao Sun, Philip S. Yu:
Lecture-style Tutorial: Towards Graph Foundation Models. WWW (Companion Volume) 2024: 1264-1267 - [c1052]Zefeng Chen, Wensheng Gan, Jiayi Sun, Jiayang Wu, Philip S. Yu:
Open Metaverse: Issues, Evolution, and Future. WWW (Companion Volume) 2024: 1351-1360 - [c1051]Wenting Zhao, Zhongfen Deng, Shweta Yadav, Philip S. Yu:
Heterogeneous Knowledge Grounding for Medical Question Answering with Retrieval Augmented Large Language Model. WWW (Companion Volume) 2024: 1590-1594 - [c1050]Li Sun, Jingbin Hu, Suyang Zhou, Zhenhao Huang, Junda Ye, Hao Peng, Zhengtao Yu, Philip S. Yu:
RicciNet: Deep Clustering via A Riemannian Generative Model. WWW 2024: 4071-4082 - [i531]Yao Wan, Yang He, Zhangqian Bi, Jianguo Zhang, Hongyu Zhang, Yulei Sui, Guandong Xu, Hai Jin, Philip S. Yu:
Deep Learning for Code Intelligence: Survey, Benchmark and Toolkit. CoRR abs/2401.00288 (2024) - [i530]Li Sun, Zhenhao Huang, Zixi Wang, Feiyang Wang, Hao Peng, Philip S. Yu:
Motif-aware Riemannian Graph Neural Network with Generative-Contrastive Learning. CoRR abs/2401.01232 (2024) - [i529]Li Sun, Junda Ye, Jiawei Zhang, Yong Yang, Mingsheng Liu, Feiyang Wang, Philip S. Yu:
Contrastive Sequential Interaction Network Learning on Co-Evolving Riemannian Spaces. CoRR abs/2401.01243 (2024) - [i528]Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yue Zhao:
TrustLLM: Trustworthiness in Large Language Models. CoRR abs/2401.05561 (2024) - [i527]Li Sun, Zhenhao Huang, Hua Wu, Junda Ye, Hao Peng, Zhengtao Yu, Philip S. Yu:
DeepRicci: Self-supervised Graph Structure-Feature Co-Refinement for Alleviating Over-squashing. CoRR abs/2401.12780 (2024) - [i526]Wenjing Chang, Kay Liu, Kaize Ding, Philip S. Yu, Jianjun Yu:
Multitask Active Learning for Graph Anomaly Detection. CoRR abs/2401.13210 (2024) - [i525]Liangwei Yang, Hengrui Zhang, Zihe Song, Jiawei Zhang, Weizhi Zhang, Jing Ma, Philip S. Yu:
Cyclic Neural Network. CoRR abs/2402.03332 (2024) - [i524]Yuqing Liu, Yu Wang, Lichao Sun, Philip S. Yu:
Rec-GPT4V: Multimodal Recommendation with Large Vision-Language Models. CoRR abs/2402.08670 (2024) - [i523]Chen Wang, Fangxin Wang, Ruocheng Guo, Yueqing Liang, Kay Liu, Philip S. Yu:
Confidence-aware Fine-tuning of Sequential Recommendation Systems via Conformal Prediction. CoRR abs/2402.08976 (2024) - [i522]Yinghui Li, Qingyu Zhou, Yuanzhen Luo, Shirong Ma, Yangning Li, Hai-Tao Zheng, Xuming Hu, Philip S. Yu:
When LLMs Meet Cunning Questions: A Fallacy Understanding Benchmark for Large Language Models. CoRR abs/2402.11100 (2024) - [i521]Xiangjue Dong, Yibo Wang, Philip S. Yu, James Caverlee:
Disclosure and Mitigation of Gender Bias in LLMs. CoRR abs/2402.11190 (2024) - [i520]Yinghui Li, Shang Qin, Jingheng Ye, Shirong Ma, Yangning Li, Libo Qin, Xuming Hu, Wenhao Jiang, Hai-Tao Zheng, Philip S. Yu:
Rethinking the Roles of Large Language Models in Chinese Grammatical Error Correction. CoRR abs/2402.11420 (2024) - [i519]Qian Ma, Hongliang Chi, Hengrui Zhang, Kay Liu, Zhiwei Zhang, Lu Cheng, Suhang Wang, Philip S. Yu, Yao Ma:
Overcoming Pitfalls in Graph Contrastive Learning Evaluation: Toward Comprehensive Benchmarks. CoRR abs/2402.15680 (2024) - [i518]Chaoguang Luo, Liuying Wen, Yong Qin, Liangwei Yang, Zhineng Hu, Philip S. Yu:
Against Filter Bubbles: Diversified Music Recommendation via Weighted Hypergraph Embedding Learning. CoRR abs/2402.16299 (2024) - [i517]Wei Ju, Siyu Yi, Yifan Wang, Zhiping Xiao, Zhengyang Mao, Hourun Li, Yiyang Gu, Yifang Qin, Nan Yin, Senzhang Wang, Xinwang Liu, Xiao Luo, Philip S. Yu, Ming Zhang:
A Survey of Graph Neural Networks in Real world: Imbalance, Noise, Privacy and OOD Challenges. CoRR abs/2403.04468 (2024) - [i516]Fangxin Wang, Yuqing Liu, Kay Liu, Yibo Wang, Sourav Medya, Philip S. Yu:
Uncertainty in Graph Neural Networks: A Survey. CoRR abs/2403.07185 (2024) - [i515]Xuming Hu, Xiaochuan Li, Junzhe Chen, Yinghui Li, Yangning Li, Xiaoguang Li, Yasheng Wang, Qun Liu, Lijie Wen, Philip S. Yu, Zhijiang Guo:
Evaluating Robustness of Generative Search Engine on Adversarial Factual Questions. CoRR abs/2403.12077 (2024) - [i514]Shen Wang, Tianlong Xu, Hang Li, Chaoli Zhang, Joleen Liang, Jiliang Tang, Philip S. Yu, Qingsong Wen:
Large Language Models for Education: A Survey and Outlook. CoRR abs/2403.18105 (2024) - [i513]Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu:
Instruction-based Hypergraph Pretraining. CoRR abs/2403.19063 (2024) - [i512]Yucheng Jin, Yun Xiong, Juncheng Fang, Xixi Wu, Dongxiao He, Xing Jia, Bingchen Zhao, Philip S. Yu:
Beyond the Known: Novel Class Discovery for Open-world Graph Learning. CoRR abs/2403.19907 (2024) - [i511]Libo Qin, Qiguang Chen, Yuhang Zhou, Zhi Chen, Yinghui Li, Lizi Liao, Min Li, Wanxiang Che, Philip S. Yu:
Multilingual Large Language Model: A Survey of Resources, Taxonomy and Frontiers. CoRR abs/2404.04925 (2024) - [i510]Pu Li, Xiaoyan Yu, Hao Peng, Yantuan Xian, Linqin Wang, Li Sun, Jingyun Zhang, Philip S. Yu:
Relational Prompt-based Pre-trained Language Models for Social Event Detection. CoRR abs/2404.08263 (2024) - [i509]Hoang H. Nguyen, Chenwei Zhang, Ye Liu, Natalie Parde, Eugene Rohrbaugh, Philip S. Yu:
CORI: CJKV Benchmark with Romanization Integration - A step towards Cross-lingual Transfer Beyond Textual Scripts. CoRR abs/2404.12618 (2024) - [i508]Hao Peng, Jingyun Zhang, Xiang Huang, Zhifeng Hao, Angsheng Li, Zhengtao Yu, Philip S. Yu:
Unsupervised Social Bot Detection via Structural Information Theory. CoRR abs/2404.13595 (2024) - [i507]Chao Chen, Chenghua Guo, Rui Xu, Xiangwen Liao, Xi Zhang, Sihong Xie, Hui Xiong, Philip S. Yu:
Uncertainty Quantification on Graph Learning: A Survey. CoRR abs/2404.14642 (2024) - [i506]Henry Peng Zou, Vinay Samuel, Yue Zhou, Weizhi Zhang, Liancheng Fang, Zihe Song, Philip S. Yu, Cornelia Caragea:
ImplicitAVE: An Open-Source Dataset and Multimodal LLMs Benchmark for Implicit Attribute Value Extraction. CoRR abs/2404.15592 (2024) - [i505]Weizhi Zhang, Liangwei Yang, Zihe Song, Henry Peng Zou, Ke Xu, Yuanjie Zhu, Philip S. Yu:
Mixed Supervised Graph Contrastive Learning for Recommendation. CoRR abs/2404.15954 (2024) - [i504]Jiayang Wu, Wensheng Gan, Han-Chieh Chao, Philip S. Yu:
Geospatial Big Data: Survey and Challenges. CoRR abs/2404.18428 (2024) - [i503]Yuwei Cao, Hao Peng, Angsheng Li, Chenyu You, Zhifeng Hao, Philip S. Yu:
Multi-Relational Structural Entropy. CoRR abs/2405.07096 (2024) - [i502]Li Sun, Zhenhao Huang, Hao Peng, Yujie Wang, Chunyang Liu, Philip S. Yu:
LSEnet: Lorentz Structural Entropy Neural Network for Deep Graph Clustering. CoRR abs/2405.11801 (2024) - [i501]Libo Qin, Qiguang Chen, Xiachong Feng, Yang Wu, Yongheng Zhang, Yinghui Li, Min Li, Wanxiang Che, Philip S. Yu:
Large Language Models Meet NLP: A Survey. CoRR abs/2405.12819 (2024) - [i500]Hanyi Xu, Wensheng Gan, Zhenlian Qi, Jiayang Wu, Philip S. Yu:
Large Language Models for Education: A Survey. CoRR abs/2405.13001 (2024) - [i499]Yanxin Zheng, Wensheng Gan, Zefeng Chen, Zhenlian Qi, Qian Liang, Philip S. Yu:
Large Language Models for Medicine: A Survey. CoRR abs/2405.13055 (2024) - [i498]Hengrui Zhang, Liancheng Fang, Philip S. Yu:
Unleashing the Potential of Diffusion Models for Incomplete Data Imputation. CoRR abs/2405.20690 (2024) - [i497]Wenjing Chang, Kay Liu, Philip S. Yu, Jianjun Yu:
Enhancing Fairness in Unsupervised Graph Anomaly Detection through Disentanglement. CoRR abs/2406.00987 (2024) - [i496]Ronghui Xu, Hao Miao, Senzhang Wang, Philip S. Yu, Jianxin Wang:
PeFAD: A Parameter-Efficient Federated Framework for Time Series Anomaly Detection. CoRR abs/2406.02318 (2024) - [i495]Xuexiong Luo, Jia Wu, Jian Yang, Shan Xue, Amin Beheshti, Quan Z. Sheng, David McAlpine, Paul F. Sowman, Alexis Giral, Philip S. Yu:
Graph Neural Networks for Brain Graph Learning: A Survey. CoRR abs/2406.02594 (2024) - [i494]Jian Zhu, Xiaoye Chen, Wensheng Gan, Zefeng Chen, Philip S. Yu:
Targeted Mining Precise-positioning Episode Rules. CoRR abs/2406.05070 (2024) - [i493]Hengzhu Liu, Ping Xiong, Tianqing Zhu, Philip S. Yu:
A Survey on Machine Unlearning: Techniques and New Emerged Privacy Risks. CoRR abs/2406.06186 (2024) - [i492]Shang Wang, Tianqing Zhu, Bo Liu, Ming Ding, Xu Guo, Dayong Ye, Wanlei Zhou, Philip S. Yu:
Unique Security and Privacy Threats of Large Language Model: A Comprehensive Survey. CoRR abs/2406.07973 (2024) - [i491]Jiawen Qin, Haonan Yuan, Qingyun Sun, Lyujin Xu, Jiaqi Yuan, Pengfeng Huang, Zhaonan Wang, Xingcheng Fu, Hao Peng, Jianxin Li, Philip S. Yu:
IGL-Bench: Establishing the Comprehensive Benchmark for Imbalanced Graph Learning. CoRR abs/2406.09870 (2024) - [i490]Laiqiao Qin, Tianqing Zhu, Wanlei Zhou, Philip S. Yu:
Knowledge Distillation in Federated Learning: a Survey on Long Lasting Challenges and New Solutions. CoRR abs/2406.10861 (2024) - [i489]Linlin Wang, Tianqing Zhu, Wanlei Zhou, Philip S. Yu:
Linkage on Security, Privacy and Fairness in Federated Learning: New Balances and New Perspectives. CoRR abs/2406.10884 (2024) - [i488]Lingzhe Zhang, Tong Jia, Mengxi Jia, Yifan Wu, Aiwei Liu, Yong Yang, Zhonghai Wu, Xuming Hu, Philip S. Yu, Ying Li:
A Survey of AIOps for Failure Management in the Era of Large Language Models. CoRR abs/2406.11213 (2024) - [i487]Haopeng Zhang, Philip S. Yu, Jiawei Zhang:
A Systematic Survey of Text Summarization: From Statistical Methods to Large Language Models. CoRR abs/2406.11289 (2024) - [i486]Heng Xu, Tianqing Zhu, Lefeng Zhang, Wanlei Zhou, Philip S. Yu:
Update Selective Parameters: Federated Machine Unlearning Based on Model Explanation. CoRR abs/2406.12516 (2024) - [i485]Yueqing Liang, Liangwei Yang, Chen Wang, Xiongxiao Xu, Philip S. Yu, Kai Shu:
Taxonomy-Guided Zero-Shot Recommendations with LLMs. CoRR abs/2406.14043 (2024) - [i484]Jiangshu Du, Yibo Wang, Wenting Zhao, Zhongfen Deng, Shuaiqi Liu, Renze Lou, Henry Peng Zou, Pranav Narayanan Venkit, Nan Zhang, Mukund Srinath, Ranran Haoran Zhang, Vipul Gupta, Yinghui Li, Tao Li, Fei Wang, Qin Liu, Tianlin Liu, Pengzhi Gao, Congying Xia, Chen Xing, Jiayang Cheng, Zhaowei Wang, Ying Su, Raj Sanjay Shah, Ruohao Guo, Jing Gu, Haoran Li, Kangda Wei, Zihao Wang, Lu Cheng, Surangika Ranathunga, Meng Fang, Jie Fu, Fei Liu, Ruihong Huang, Eduardo Blanco, Yixin Cao, Rui Zhang, Philip S. Yu, Wenpeng Yin:
LLMs Assist NLP Researchers: Critique Paper (Meta-)Reviewing. CoRR abs/2406.16253 (2024) - [i483]Faqian Guan, Tianqing Zhu, Hui Sun, Wanlei Zhou, Philip S. Yu:
Large Language Models for Link Stealing Attacks Against Graph Neural Networks. CoRR abs/2406.16963 (2024) - [i482]Qingyun Sun, Ziying Chen, Beining Yang, Cheng Ji, Xingcheng Fu, Sheng Zhou, Hao Peng, Jianxin Li, Philip S. Yu:
GC-Bench: An Open and Unified Benchmark for Graph Condensation. CoRR abs/2407.00615 (2024) - [i481]Weizhi Zhang, Liangwei Yang, Zihe Song, Henry Peng Zou, Ke Xu, Liancheng Fang, Philip S. Yu:
Do We Really Need Graph Convolution During Training? Light Post-Training Graph-ODE for Efficient Recommendation. CoRR abs/2407.18910 (2024) - [i480]Feng He, Tianqing Zhu, Dayong Ye, Bo Liu, Wanlei Zhou, Philip S. Yu:
The Emerged Security and Privacy of LLM Agent: A Survey with Case Studies. CoRR abs/2407.19354 (2024) - [i479]Liangwei Yang, Zhiwei Liu, Jianguo Zhang, Rithesh Murthy, Shelby Heinecke, Huan Wang, Caiming Xiong, Philip S. Yu:
Personalized Multi-task Training for Recommender System. CoRR abs/2407.21364 (2024) - [i478]Yujie Feng, Xu Chu, Yongxin Xu, Zexin Lu, Bo Liu, Philip S. Yu, Xiao-Ming Wu:
TaSL: Task Skill Localization and Consolidation for Language Model Continual Learning. CoRR abs/2408.05200 (2024) - [i477]Wendi Chen, Wensheng Gan, Philip S. Yu:
Digital Fingerprinting on Multimedia: A Survey. CoRR abs/2408.14155 (2024) - [i476]Yuqing Liang, Jiancheng Xiao, Wensheng Gan, Philip S. Yu:
Watermarking Techniques for Large Language Models: A Survey. CoRR abs/2409.00089 (2024) - [i475]Xiaoyan Yu, Yifan Wei, Pu Li, Shuaishuai Zhou, Hao Peng, Li Sun, Liehuang Zhu, Philip S. Yu:
DAMe: Personalized Federated Social Event Detection with Dual Aggregation Mechanism. CoRR abs/2409.00614 (2024) - [i474]Leyi Pan, Aiwei Liu, Yijian Lu, Zitian Gao, Yichen Di, Lijie Wen, Irwin King, Philip S. Yu:
WaterSeeker: Efficient Detection of Watermarked Segments in Large Documents. CoRR abs/2409.05112 (2024) - [i473]Yujia Zhou, Yan Liu, Xiaoxi Li, Jiajie Jin, Hongjin Qian, Zheng Liu, Chaozhuo Li, Zhicheng Dou, Tsung-Yi Ho, Philip S. Yu:
Trustworthiness in Retrieval-Augmented Generation Systems: A Survey. CoRR abs/2409.10102 (2024) - [i472]Aiwei Liu, Sheng Guan, Yiming Liu, Leyi Pan, Yifei Zhang, Liancheng Fang, Lijie Wen, Philip S. Yu, Xuming Hu:
Can Watermarked LLMs be Identified by Users via Crafted Prompts? CoRR abs/2410.03168 (2024) - [i471]Aiwei Liu, Haoping Bai, Zhiyun Lu, Yanchao Sun, Xiang Kong, Simon Wang, Jiulong Shan, Albin Madappally Jose, Xiaojiang Liu, Lijie Wen, Philip S. Yu, Meng Cao:
TIS-DPO: Token-level Importance Sampling for Direct Preference Optimization With Estimated Weights. CoRR abs/2410.04350 (2024) - [i470]Yibo Yan, Shen Wang, Jiahao Huo, Hang Li, Boyan Li, Jiamin Su, Xiong Gao, Yifan Zhang, Tianlong Xu, Zhendong Chu, Aoxiao Zhong, Kun Wang, Hui Xiong, Philip S. Yu, Xuming Hu, Qingsong Wen:
ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detection. CoRR abs/2410.04509 (2024) - [i469]Wooseong Yang, Chen Wang, Zihe Song, Weizhi Zhang, Philip S. Yu:
Item Cluster-aware Prompt Learning for Session-based Recommendation. CoRR abs/2410.04756 (2024) - [i468]Dianzhi Yu, Xinni Zhang, Yankai Chen, Aiwei Liu, Yifei Zhang, Philip S. Yu, Irwin King:
Recent Advances of Multimodal Continual Learning: A Comprehensive Survey. CoRR abs/2410.05352 (2024) - [i467]Yuhang Yao, Yuan Li, Xinyi Fan, Junhao Li, Kay Liu, Weizhao Jin, Srivatsan Ravi, Philip S. Yu, Carlee Joe-Wong:
FedGraph: A Research Library and Benchmark for Federated Graph Learning. CoRR abs/2410.06340 (2024) - [i466]Fangxin Wang, Kay Liu, Sourav Medya, Philip S. Yu:
BANGS: Game-Theoretic Node Selection for Graph Self-Training. CoRR abs/2410.09348 (2024) - [i465]Haoyan Xu, Kay Liu, Zhengtao Yao, Philip S. Yu, Kaize Ding, Yue Zhao:
LEGO-Learn: Label-Efficient Graph Open-Set Learning. CoRR abs/2410.16386 (2024) - [i464]Li Sun, Zhenhao Huang, Qiqi Wan, Hao Peng, Philip S. Yu:
Spiking Graph Neural Network on Riemannian Manifolds. CoRR abs/2410.17941 (2024) - [i463]Hengrui Zhang, Liancheng Fang, Qitian Wu, Philip S. Yu:
Diffusion-nested Auto-Regressive Synthesis of Heterogeneous Tabular Data. CoRR abs/2410.21523 (2024) - [i462]Hoang Nguyen, Khyati Mahajan, Vikas Yadav, Philip S. Yu, Masoud Hashemi, Rishabh Maheshwary:
Prompting with Phonemes: Enhancing LLM Multilinguality for non-Latin Script Languages. CoRR abs/2411.02398 (2024) - [i461]Tao Zhang, Ning Yan, Masood Mortazavi, Hoang H. Nguyen, Zhongfen Deng, Philip S. Yu:
Graph-DPEP: Decomposed Plug and Ensemble Play for Few-Shot Document Relation Extraction with Graph-of-Thoughts Reasoning. CoRR abs/2411.02864 (2024) - [i460]Yangning Li, Yinghui Li, Xinyu Wang, Yong Jiang, Zhen Zhang, Xinran Zheng, Hui Wang, Hai-Tao Zheng, Pengjun Xie, Philip S. Yu, Fei Huang, Jingren Zhou:
Benchmarking Multimodal Retrieval Augmented Generation with Dynamic VQA Dataset and Self-adaptive Planning Agent. CoRR abs/2411.02937 (2024) - [i459]Mengmeng Yang, Tianqing Zhu, Chi Liu, Wanlei Zhou, Shui Yu, Philip S. Yu:
New Emerged Security and Privacy of Pre-trained Model: a Survey and Outlook. CoRR abs/2411.07691 (2024) - [i458]Zhichen Zeng, Xiaolong Liu, Mengyue Hang, Xiaoyi Liu, Qinghai Zhou, Chaofei Yang, Yiqun Liu, Yichen Ruan, Laming Chen, Yuxin Chen, Yujia Hao, Jiaqi Xu, Jade Nie, Xi Liu, Buyun Zhang, Wei Wen, Siyang Yuan, Kai Wang, Wen-Yen Chen, Yiping Han, Huayu Li, Chunzhi Yang, Bo Long, Philip S. Yu, Hanghang Tong, Jiyan Yang:
InterFormer: Towards Effective Heterogeneous Interaction Learning for Click-Through Rate Prediction. CoRR abs/2411.09852 (2024) - [i457]Xiaolong Liu, Zhichen Zeng, Xiaoyi Liu, Siyang Yuan, Weinan Song, Mengyue Hang, Yiqun Liu, Chaofei Yang, Donghyun Kim, Wen-Yen Chen, Jiyan Yang, Yiping Han, Rong Jin, Bo Long, Hanghang Tong, Philip S. Yu:
A Collaborative Ensemble Framework for CTR Prediction. CoRR abs/2411.13700 (2024) - [i456]Diandian Guo, Cong Cao, Fangfang Yuan, Yanbing Liu, Guangjie Zeng, Xiaoyan Yu, Hao Peng, Philip S. Yu:
Multi-View Incongruity Learning for Multimodal Sarcasm Detection. CoRR abs/2412.00756 (2024) - [i455]Kay Liu, Jiahao Ding, MohamadAli Torkamani, Philip S. Yu:
TGTOD: A Global Temporal Graph Transformer for Outlier Detection at Scale. CoRR abs/2412.00984 (2024) - [i454]Yang Wu, Yao Wan, Zhaoyang Chu, Wenting Zhao, Ye Liu, Hongyu Zhang, Xuanhua Shi, Philip S. Yu:
Can Large Language Models Serve as Evaluators for Code Summarization? CoRR abs/2412.01333 (2024) - [i453]Yuwei Cao, Liangwei Yang, Zhiwei Liu, Yuqing Liu, Chen Wang, Yueqing Liang, Hao Peng, Philip S. Yu:
Graph-Sequential Alignment and Uniformity: Toward Enhanced Recommendation Systems. CoRR abs/2412.04276 (2024) - [i452]Lincan Li, Jiaqi Li, Catherine Chen, Fred Gui, Hongjia Yang, Chenxiao Yu, Zhengguang Wang, Jianing Cai, Junlong Aaron Zhou, Bolin Shen, Alex Qian, Weixin Chen, Zhongkai Xue, Lichao Sun, Lifang He, Hanjie Chen, Kaize Ding, Zijian Du, Fangzhou Mu, Jiaxin Pei, Jieyu Zhao, Swabha Swayamdipta, Willie Neiswanger, Hua Wei, Xiyang Hu, Shixiang Zhu, Tianlong Chen, Yingzhou Lu, Yang Shi, Lianhui Qin, Tianfan Fu, Zhengzhong Tu, Yuzhe Yang, Jaemin Yoo, Jiaheng Zhang, Ryan A. Rossi, Liang Zhan, Liang Zhao, Emilio Ferrara, Yan Liu, Furong Huang, Xiangliang Zhang, Lawrence Rothenberg, Shuiwang Ji, Philip S. Yu, Yue Zhao, Yushun Dong:
Political-LLM: Large Language Models in Political Science. CoRR abs/2412.06864 (2024) - [i451]Xiang Huang, Hao Peng, Li Sun, Hui Lin, Chunyang Liu, Jiang Cao, Philip S. Yu:
Structural Entropy Guided Probabilistic Coding. CoRR abs/2412.08841 (2024) - [i450]Xiaoyan Yu, Yifan Wei, Shuaishuai Zhou, Zhiwei Yang, Li Sun, Hao Peng, Liehuang Zhu, Philip S. Yu:
Towards Effective, Efficient and Unsupervised Social Event Detection in the Hyperbolic Space. CoRR abs/2412.10712 (2024) - [i449]Kun Zhang, Xiaoyan Yu, Pu Li, Hao Peng, Philip S. Yu:
SocialED: A Python Library for Social Event Detection. CoRR abs/2412.13472 (2024) - [i448]Xuan Lin, Long Chen, Yile Wang, Xiangxiang Zeng, Philip S. Yu:
Property Enhanced Instruction Tuning for Multi-task Molecule Generation with Large Language Models. CoRR abs/2412.18084 (2024) - 2023
- [j528]Xuan Lin, Lichang Dai, Yafang Zhou, Zu-Guo Yu, Wen Zhang, Jian-Yu Shi, Dong-Sheng Cao, Li Zeng, Haowen Chen, Bosheng Song, Philip S. Yu, Xiangxiang Zeng:
Comprehensive evaluation of deep and graph learning on drug-drug interactions prediction. Briefings Bioinform. 24(4) (2023) - [j527]Shuai Zhou, Chi Liu, Dayong Ye, Tianqing Zhu, Wanlei Zhou, Philip S. Yu:
Adversarial Attacks and Defenses in Deep Learning: From a Perspective of Cybersecurity. ACM Comput. Surv. 55(8): 163:1-163:39 (2023) - [j526]Guiling Li, Shaolin Xu, Senzhang Wang, Philip S. Yu:
Forest based on Interval Transformation (FIT): A time series classifier with adaptive features. Expert Syst. Appl. 213(Part C): 118923 (2023) - [j525]Chengcheng Sun, Zhixiao Wang, Xiaobin Rui, Philip S. Yu, Lichao Sun:
An in-depth study on key nodes in social networks. Intell. Data Anal. 27(6): 1811-1838 (2023) - [j524]Chuanren Liu, Ehsan Fakharizadi, Tong Xu, Philip S. Yu:
Recent advances in domain-driven data mining. Int. J. Data Sci. Anal. 15(1): 1-7 (2023) - [j523]Zhimeng Yang, Yazhou Ren, Zirui Wu, Ming Zeng, Jie Xu, Yang Yang, Xiaorong Pu, Philip S. Yu, Lifang He:
DC-FUDA: Improving deep clustering via fully unsupervised domain adaptation. Neurocomputing 526: 109-120 (2023) - [j522]Junsan Zhang, Xiaomin Wang, Yao Wan, Leiquan Wang, Jian Wang, Philip S. Yu:
SOR-TC: Self-attentive octave ResNet with temporal consistency for compressed video action recognition. Neurocomputing 533: 191-205 (2023) - [j521]Jiayi Sun, Wensheng Gan, Han-Chieh Chao, Philip S. Yu, Weiping Ding:
Internet of Behaviors: A Survey. IEEE Internet Things J. 10(13): 11117-11134 (2023) - [j520]Yao Chen, Wensheng Gan, Yongdong Wu, Philip S. Yu:
Privacy-preserving federated mining of frequent itemsets. Inf. Sci. 625: 504-520 (2023) - [j519]Tao Zhang, Tianqing Zhu, Mengde Han, Fengwen Chen, Jing Li, Wanlei Zhou, Philip S. Yu:
Fairness in graph-based semi-supervised learning. Knowl. Inf. Syst. 65(2): 543-570 (2023) - [j518]Xingcheng Fu, Jianxin Li, Jia Wu, Jiawen Qin, Qingyun Sun, Cheng Ji, Senzhang Wang, Hao Peng, Philip S. Yu:
Adaptive curvature exploration geometric graph neural network. Knowl. Inf. Syst. 65(5): 2281-2304 (2023) - [j517]Huan Tian, Bo Liu, Tianqing Zhu, Wanlei Zhou, Philip S. Yu:
CIFair: Constructing continuous domains of invariant features for image fair classifications. Knowl. Based Syst. 268: 110417 (2023) - [j516]Tao Zhang, Tianqing Zhu, Jing Li, Wanlei Zhou, Philip S. Yu:
Revisiting model fairness via adversarial examples. Knowl. Based Syst. 277: 110777 (2023) - [j515]Zishuo Cheng, Tianqing Zhu, Congcong Zhu, Dayong Ye, Wanlei Zhou, Philip S. Yu:
Privacy and evolutionary cooperation in neural-network-based game theory. Knowl. Based Syst. 282: 111076 (2023) - [j514]Hao Peng, Ruitong Zhang, Shaoning Li, Yuwei Cao, Shirui Pan, Philip S. Yu:
Reinforced, Incremental and Cross-Lingual Event Detection From Social Messages. IEEE Trans. Pattern Anal. Mach. Intell. 45(1): 980-998 (2023) - [j513]Yunbo Wang, Haixu Wu, Jianjin Zhang, Zhifeng Gao, Jianmin Wang, Philip S. Yu, Mingsheng Long:
PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning. IEEE Trans. Pattern Anal. Mach. Intell. 45(2): 2208-2225 (2023) - [j512]Jianxin Li, Qingyun Sun, Hao Peng, Beining Yang, Jia Wu, Philip S. Yu:
Adaptive Subgraph Neural Network With Reinforced Critical Structure Mining. IEEE Trans. Pattern Anal. Mach. Intell. 45(7): 8063-8080 (2023) - [j511]Yang Shu, Zhangjie Cao, Jinghan Gao, Jianmin Wang, Philip S. Yu, Mingsheng Long:
Omni-Training: Bridging Pre-Training and Meta-Training for Few-Shot Learning. IEEE Trans. Pattern Anal. Mach. Intell. 45(12): 15275-15291 (2023) - [j510]Wensheng Gan, Jerry Chun-Wei Lin, Han-Chieh Chao, Philip S. Yu:
Discovering High Utility Episodes in Sequences. IEEE Trans. Artif. Intell. 4(3): 473-486 (2023) - [j509]Tao Zhang, Congying Xia, Zhiwei Liu, Shu Zhao, Hao Peng, Philip S. Yu:
Domain-Invariant Feature Progressive Distillation with Adversarial Adaptive Augmentation for Low-Resource Cross-Domain NER. ACM Trans. Asian Low Resour. Lang. Inf. Process. 22(3): 76:1-76:21 (2023) - [j508]Shu'ang Li, Xuming Hu, Li Lin, Aiwei Liu, Lijie Wen, Philip S. Yu:
A Multi-Level Supervised Contrastive Learning Framework for Low-Resource Natural Language Inference. IEEE ACM Trans. Audio Speech Lang. Process. 31: 1771-1783 (2023) - [j507]Xiao Wang, Deyu Bo, Chuan Shi, Shaohua Fan, Yanfang Ye, Philip S. Yu:
A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources. IEEE Trans. Big Data 9(2): 415-436 (2023) - [j506]Chunkai Zhang, Quanjian Dai, Zilin Du, Wensheng Gan, Jian Weng, Philip S. Yu:
TUSQ: Targeted High-Utility Sequence Querying. IEEE Trans. Big Data 9(2): 512-527 (2023) - [j505]Xuan Lin, Zhe Quan, Zhi-Jie Wang, Yan Guo, Xiangxiang Zeng, Philip S. Yu:
Effectively Identifying Compound-Protein Interaction Using Graph Neural Representation. IEEE ACM Trans. Comput. Biol. Bioinform. 20(2): 932-943 (2023) - [j504]Yan Kang, Haining Wang, Bin Pu, Liu Tao, Jianguo Chen, Philip S. Yu:
A Hybrid Two-Stage Teaching-Learning-Based Optimization Algorithm for Feature Selection in Bioinformatics. IEEE ACM Trans. Comput. Biol. Bioinform. 20(3): 1746-1760 (2023) - [j503]Tingting Liang, Congying Xia, Ziqiang Zhao, Yixuan Jiang, Yuyu Yin, Philip S. Yu:
Transferring From Textual Entailment to Biomedical Named Entity Recognition. IEEE ACM Trans. Comput. Biol. Bioinform. 20(4): 2577-2586 (2023) - [j502]Ling Huang, Chang-Dong Wang, Philip S. Yu:
Higher Order Connection Enhanced Community Detection in Adversarial Multiview Networks. IEEE Trans. Cybern. 53(5): 3060-3074 (2023) - [j501]Li Sun, Zhongbao Zhang, Gen Li, Pengxin Ji, Sen Su, Philip S. Yu:
MC2: Unsupervised Multiple Social Network Alignment. ACM Trans. Intell. Syst. Technol. 14(4): 70:1-70:22 (2023) - [j500]Gengsen Huang, Wensheng Gan, Jian Weng, Philip S. Yu:
US-Rule: Discovering Utility-driven Sequential Rules. ACM Trans. Knowl. Discov. Data 17(1): 10:1-10:22 (2023) - [j499]Jie Yang, Zhixiao Wang, Xiaobin Rui, Yahui Chai, Philip S. Yu, Lichao Sun:
Triadic Closure Sensitive Influence Maximization. ACM Trans. Knowl. Discov. Data 17(6): 77:1-77:26 (2023) - [j498]Houye Ji, Xiao Wang, Chuan Shi, Bai Wang, Philip S. Yu:
Heterogeneous Graph Propagation Network. IEEE Trans. Knowl. Data Eng. 35(1): 521-532 (2023) - [j497]Jianxin Li, Hao Peng, Yuwei Cao, Yingtong Dou, Hekai Zhang, Philip S. Yu, Lifang He:
Higher-Order Attribute-Enhancing Heterogeneous Graph Neural Networks. IEEE Trans. Knowl. Data Eng. 35(1): 560-574 (2023) - [j496]Di Jin, Zhizhi Yu, Pengfei Jiao, Shirui Pan, Dongxiao He, Jia Wu, Philip S. Yu, Weixiong Zhang:
A Survey of Community Detection Approaches: From Statistical Modeling to Deep Learning. IEEE Trans. Knowl. Data Eng. 35(2): 1149-1170 (2023) - [j495]Dongxiao He, Tao Wang, Lu Zhai, Di Jin, Liang Yang, Yuxiao Huang, Zhiyong Feng, Philip S. Yu:
Adversarial Representation Mechanism Learning for Network Embedding. IEEE Trans. Knowl. Data Eng. 35(2): 1200-1213 (2023) - [j494]Qiaomin Yi, Ning Yang, Philip S. Yu:
Dual Adversarial Variational Embedding for Robust Recommendation. IEEE Trans. Knowl. Data Eng. 35(2): 1421-1433 (2023) - [j493]Lu Bai, Yuhang Jiao, Lixin Cui, Luca Rossi, Yue Wang, Philip S. Yu, Edwin R. Hancock:
Learning Graph Convolutional Networks Based on Quantum Vertex Information Propagation. IEEE Trans. Knowl. Data Eng. 35(2): 1747-1760 (2023) - [j492]Shu Zhao, Ziwei Du, Jie Chen, Yanping Zhang, Jie Tang, Philip S. Yu:
Hierarchical Representation Learning for Attributed Networks. IEEE Trans. Knowl. Data Eng. 35(3): 2641-2656 (2023) - [j491]Hao Peng, Jianxin Li, Zheng Wang, Renyu Yang, Mingsheng Liu, Mingming Zhang, Philip S. Yu, Lifang He:
Lifelong Property Price Prediction: A Case Study for the Toronto Real Estate Market. IEEE Trans. Knowl. Data Eng. 35(3): 2765-2780 (2023) - [j490]Pinghua Xu, Wenbin Hu, Jia Wu, Weiwei Liu, Yang Yang, Philip S. Yu:
Signed Network Representation by Preserving Multi-Order Signed Proximity. IEEE Trans. Knowl. Data Eng. 35(3): 3087-3100 (2023) - [j489]Zhenyu Qiu, Jia Wu, Wenbin Hu, Bo Du, Guocai Yuan, Philip S. Yu:
Temporal Link Prediction With Motifs for Social Networks. IEEE Trans. Knowl. Data Eng. 35(3): 3145-3158 (2023) - [j488]Lefeng Zhang, Tianqing Zhu, Ping Xiong, Wanlei Zhou, Philip S. Yu:
A Robust Game-Theoretical Federated Learning Framework With Joint Differential Privacy. IEEE Trans. Knowl. Data Eng. 35(4): 3333-3346 (2023) - [j487]Di Jin, Zhizhi Yu, Dongxiao He, Carl Yang, Philip S. Yu, Jiawei Han:
GCN for HIN via Implicit Utilization of Attention and Meta-Paths. IEEE Trans. Knowl. Data Eng. 35(4): 3925-3937 (2023) - [j486]Xusheng Zhao, Qiong Dai, Jia Wu, Hao Peng, Mingsheng Liu, Xu Bai, Jianlong Tan, Senzhang Wang, Philip S. Yu:
Multi-View Tensor Graph Neural Networks Through Reinforced Aggregation. IEEE Trans. Knowl. Data Eng. 35(4): 4077-4091 (2023) - [j485]Xiaoming Liu, Zhanwei Zhang, Lingjuan Lyu, Zhaohan Zhang, Shuai Xiao, Chao Shen, Philip S. Yu:
Traffic Anomaly Prediction Based on Joint Static-Dynamic Spatio-Temporal Evolutionary Learning. IEEE Trans. Knowl. Data Eng. 35(5): 5356-5370 (2023) - [j484]Li Sun, Zhongbao Zhang, Feiyang Wang, Pengxin Ji, Jian Wen, Sen Su, Philip S. Yu:
Aligning Dynamic Social Networks: An Optimization Over Dynamic Graph Autoencoder. IEEE Trans. Knowl. Data Eng. 35(6): 5597-5611 (2023) - [j483]Jiyue Li, Senzhang Wang, Jiaqiang Zhang, Hao Miao, Junbo Zhang, Philip S. Yu:
Fine-Grained Urban Flow Inference With Incomplete Data. IEEE Trans. Knowl. Data Eng. 35(6): 5851-5864 (2023) - [j482]Yixin Liu, Ming Jin, Shirui Pan, Chuan Zhou, Yu Zheng, Feng Xia, Philip S. Yu:
Graph Self-Supervised Learning: A Survey. IEEE Trans. Knowl. Data Eng. 35(6): 5879-5900 (2023) - [j481]Gaoyang Guo, Chaokun Wang, Bencheng Yan, Yunkai Lou, Hao Feng, Junchao Zhu, Jun Chen, Fei He, Philip S. Yu:
Learning Adaptive Node Embeddings Across Graphs. IEEE Trans. Knowl. Data Eng. 35(6): 6028-6042 (2023) - [j480]Tengfei Ma, Xuan Lin, Bosheng Song, Philip S. Yu, Xiangxiang Zeng:
KG-MTL: Knowledge Graph Enhanced Multi-Task Learning for Molecular Interaction. IEEE Trans. Knowl. Data Eng. 35(7): 7068-7081 (2023) - [j479]Daokun Zhang, Jie Yin, Philip S. Yu:
Link Prediction with Contextualized Self-Supervision. IEEE Trans. Knowl. Data Eng. 35(7): 7138-7151 (2023) - [j478]Jie Xu, Yazhou Ren, Huayi Tang, Zhimeng Yang, Lili Pan, Yang Yang, Xiaorong Pu, Philip S. Yu, Lifang He:
Self-Supervised Discriminative Feature Learning for Deep Multi-View Clustering. IEEE Trans. Knowl. Data Eng. 35(7): 7470-7482 (2023) - [j477]Lichao Sun, Yingtong Dou, Carl Yang, Kai Zhang, Ji Wang, Philip S. Yu, Lifang He, Bo Li:
Adversarial Attack and Defense on Graph Data: A Survey. IEEE Trans. Knowl. Data Eng. 35(8): 7693-7711 (2023) - [j476]Jindong Wang, Cuiling Lan, Chang Liu, Yidong Ouyang, Tao Qin, Wang Lu, Yiqiang Chen, Wenjun Zeng, Philip S. Yu:
Generalizing to Unseen Domains: A Survey on Domain Generalization. IEEE Trans. Knowl. Data Eng. 35(8): 8052-8072 (2023) - [j475]Tingting Liang, Congying Xia, Haoran Xu, Ziqiang Zhao, Yuyu Yin, Liang Chen, Philip S. Yu:
Modeling Reviews for Few-Shot Recommendation via Enhanced Prototypical Network. IEEE Trans. Knowl. Data Eng. 35(9): 9407-9420 (2023) - [j474]Yang Gao, Peng Zhang, Chuan Zhou, Hong Yang, Zhao Li, Yue Hu, Philip S. Yu:
HGNAS++: Efficient Architecture Search for Heterogeneous Graph Neural Networks. IEEE Trans. Knowl. Data Eng. 35(9): 9448-9461 (2023) - [j473]Ziwen Du, Ning Yang, Zhonghua Yu, Philip S. Yu:
Learning From Atypical Behavior: Temporary Interest Aware Recommendation Based on Reinforcement Learning. IEEE Trans. Knowl. Data Eng. 35(10): 9824-9835 (2023) - [j472]Chaozhuo Li, Senzhang Wang, Jie Xu, Zheng Liu, Hao Wang, Xing Xie, Lei Chen, Philip S. Yu:
Semi-Supervised Variational User Identity Linkage via Noise-Aware Self-Learning. IEEE Trans. Knowl. Data Eng. 35(10): 10166-10180 (2023) - [j471]Lefeng Zhang, Tianqing Zhu, Ping Xiong, Wanlei Zhou, Philip S. Yu:
A Game-Theoretic Federated Learning Framework for Data Quality Improvement. IEEE Trans. Knowl. Data Eng. 35(11): 10952-10966 (2023) - [j470]Jianxin Li, Xingcheng Fu, Shijie Zhu, Hao Peng, Senzhang Wang, Qingyun Sun, Philip S. Yu, Lifang He:
A Robust and Generalized Framework for Adversarial Graph Embedding. IEEE Trans. Knowl. Data Eng. 35(11): 11004-11018 (2023) - [j469]Yicong Li, Hongxu Chen, Yile Li, Lin Li, Philip S. Yu, Guandong Xu:
Reinforcement Learning Based Path Exploration for Sequential Explainable Recommendation. IEEE Trans. Knowl. Data Eng. 35(11): 11801-11814 (2023) - [j468]Jianxin Li, Lifang He, Hao Peng, Peng Cui, Charu C. Aggarwal, Philip S. Yu:
Guest Editorial Introduction to the Special Issue on Anomaly Detection in Emerging Data-Driven Applications: Theory, Algorithms, and Applications. IEEE Trans. Knowl. Data Eng. 35(12): 11982-11983 (2023) - [j467]Mengzhu Sun, Xi Zhang, Jianqiang Ma, Sihong Xie, Yazheng Liu, Philip S. Yu:
Inconsistent Matters: A Knowledge-Guided Dual-Consistency Network for Multi-Modal Rumor Detection. IEEE Trans. Knowl. Data Eng. 35(12): 12736-12749 (2023) - [j466]Bao-Yu Liu, Ling Huang, Chang-Dong Wang, Jian-Huang Lai, Philip S. Yu:
Multiview Clustering via Proximity Learning in Latent Representation Space. IEEE Trans. Neural Networks Learn. Syst. 34(2): 973-986 (2023) - [j465]Qi Wang, Weiliang Zhao, Jian Yang, Jia Wu, Shan Xue, Qianli Xing, Philip S. Yu:
C-DeepTrust: A Context-Aware Deep Trust Prediction Model in Online Social Networks. IEEE Trans. Neural Networks Learn. Syst. 34(6): 2767-2780 (2023) - [j464]Tao Zhang, Tianqing Zhu, Kun Gao, Wanlei Zhou, Philip S. Yu:
Balancing Learning Model Privacy, Fairness, and Accuracy With Early Stopping Criteria. IEEE Trans. Neural Networks Learn. Syst. 34(9): 5557-5569 (2023) - [j463]Dayong Ye, Tianqing Zhu, Congcong Zhu, Wanlei Zhou, Philip S. Yu:
Model-Based Self-Advising for Multi-Agent Learning. IEEE Trans. Neural Networks Learn. Syst. 34(10): 7934-7945 (2023) - [j462]Zhi-Hong Deng, Chang-Dong Wang, Ling Huang, Jian-Huang Lai, Philip S. Yu:
G3SR: Global Graph Guided Session-Based Recommendation. IEEE Trans. Neural Networks Learn. Syst. 34(12): 9671-9684 (2023) - [j461]Yiqi Wang, Chaozhuo Li, Zheng Liu, Mingzheng Li, Jiliang Tang, Xing Xie, Lei Chen, Philip S. Yu:
An Adaptive Graph Pre-training Framework for Localized Collaborative Filtering. ACM Trans. Inf. Syst. 41(2): 43:1-43:27 (2023) - [j460]Tianqing Zhu, Dayong Ye, Zishuo Cheng, Wanlei Zhou, Philip S. Yu:
Learning Games for Defending Advanced Persistent Threats in Cyber Systems. IEEE Trans. Syst. Man Cybern. Syst. 53(4): 2410-2422 (2023) - [j459]Hao Peng, Jian Yang, Jia Wu, Philip S. Yu:
Introduction to the Special Issue on Advanced Graph Mining on the Web: Theory, Algorithms, and Applications: Part 1. ACM Trans. Web 17(3): 14:1-14:2 (2023) - [c1049]Li Sun, Junda Ye, Hao Peng, Feiyang Wang, Philip S. Yu:
Self-Supervised Continual Graph Learning in Adaptive Riemannian Spaces. AAAI 2023: 4633-4642 - [c1048]Qingyun Sun, Jianxin Li, Beining Yang, Xingcheng Fu, Hao Peng, Philip S. Yu:
Self-Organization Preserved Graph Structure Learning with Principle of Relevant Information. AAAI 2023: 4643-4651 - [c1047]Jiangshu Du, Wenpeng Yin, Congying Xia, Philip S. Yu:
Learning to Select from Multiple Options. AAAI 2023: 12754-12762 - [c1046]Xuming Hu, Zhijiang Guo, Zhiyang Teng, Irwin King, Philip S. Yu:
Multimodal Relation Extraction with Cross-Modal Retrieval and Synthesis. ACL (2) 2023: 303-311 - [c1045]Fukun Ma, Xuming Hu, Aiwei Liu, Yawen Yang, Shuang Li, Philip S. Yu, Lijie Wen:
AMR-based Network for Aspect-based Sentiment Analysis. ACL (1) 2023: 322-337 - [c1044]Shuang Li, Xuming Hu, Aiwei Liu, Yawen Yang, Fukun Ma, Philip S. Yu, Lijie Wen:
Enhancing Cross-lingual Natural Language Inference by Soft Prompting with Multilingual Verbalizer. ACL (Findings) 2023: 1361-1374 - [c1043]Xuming Hu, Shen Wang, Xiao Qin, Chuan Lei, Zhengyuan Shen, Christos Faloutsos, Asterios Katsifodimos, George Karypis, Lijie Wen, Philip S. Yu:
Automatic Table Union Search with Tabular Representation Learning. ACL (Findings) 2023: 3786-3800 - [c1042]Xuming Hu, Yong Jiang, Aiwei Liu, Zhongqiang Huang, Pengjun Xie, Fei Huang, Lijie Wen, Philip S. Yu:
Entity-to-Text based Data Augmentation for various Named Entity Recognition Tasks. ACL (Findings) 2023: 9072-9087 - [c1041]Hoang Nguyen, Chenwei Zhang, Tao Zhang, Eugene Rohrbaugh, Philip S. Yu:
Enhancing Cross-lingual Transfer via Phonemic Transcription Integration. ACL (Findings) 2023: 9163-9175 - [c1040]Xuming Hu, Aiwei Liu, Zeqi Tan, Xin Zhang, Chenwei Zhang, Irwin King, Philip S. Yu:
GDA: Generative Data Augmentation Techniques for Relation Extraction Tasks. ACL (Findings) 2023: 10221-10234 - [c1039]Shen Wang, Ziwei Fan, Jibing Gong, Xiaokai Wei, Philip S. Yu:
TRANSGNN: Towards Knowledge Enhanced Top-K Recommendation via Transformed Heterogeneous Graph Neural Network. IEEE Big Data 2023: 304-314 - [c1038]Xiaolong Liu, Liangwei Yang, Zhiwei Liu, Xiaohan Li, Mingdai Yang, Chen Wang, Philip S. Yu:
Group-Aware Interest Disentangled Dual-Training for Personalized Recommendation. IEEE Big Data 2023: 393-402 - [c1037]Weizhi Zhang, Liangwei Yang, Yuwei Cao, Ke Xu, Yuanjie Zhu, Philip S. Yu:
Dual-Teacher Knowledge Distillation for Strict Cold-Start Recommendation. IEEE Big Data 2023: 483-492 - [c1036]Zhongfen Deng, Seunghyun Yoon, Trung Bui, Franck Dernoncourt, Quan Hung Tran, Shuaiqi Liu, Wenting Zhao, Tao Zhang, Yibo Wang, Philip S. Yu:
Aspect-based Meeting Transcript Summarization: A Two-Stage Approach with Weak Supervision on Sentence Classification. IEEE Big Data 2023: 636-645 - [c1035]Zhongfen Deng, Hao Peng, Tao Zhang, Shuaiqi Liu, Wenting Zhao, Yibo Wang, Philip S. Yu:
JPAVE: A Generation and Classification-based Model for Joint Product Attribute Prediction and Value Extraction. IEEE Big Data 2023: 1087-1094 - [c1034]Jiayang Wu, Wensheng Gan, Zefeng Chen, Shicheng Wan, Philip S. Yu:
Multimodal Large Language Models: A Survey. IEEE Big Data 2023: 2247-2256 - [c1033]Hong Lin, Zirun Gan, Wensheng Gan, Zhenlian Qi, Yuehua Wang, Philip S. Yu:
Interaction in Metaverse: A Survey. IEEE Big Data 2023: 2473-2482 - [c1032]Wensheng Gan, Shicheng Wan, Philip S. Yu:
Model-as-a-Service (MaaS): A Survey. IEEE Big Data 2023: 4636-4645 - [c1031]Xiaolong Liu, Liangwei Yang, Chen Wang, Mingdai Yang, Zhiwei Liu, Philip S. Yu:
Multi-View Graph Convolution for Participant Recommendation. IEEE Big Data 2023: 5647-5656 - [c1030]Hong Lin, Wensheng Gan, Gengsen Huang, Philip S. Yu:
USER: Towards High-Utility Sequential Rules with Repetitive Items. IEEE Big Data 2023: 5977-5986 - [c1029]Ziwei Fan, Zhiwei Liu, Shelby Heinecke, Jianguo Zhang, Huan Wang, Caiming Xiong, Philip S. Yu:
Zero-shot Item-based Recommendation via Multi-task Product Knowledge Graph Pre-Training. CIKM 2023: 483-493 - [c1028]Hsu-Chao Lai, Philip S. Yu, Jiun-Long Huang:
Learning the Co-evolution Process on Live Stream Platforms with Dual Self-attention for Next-topic Recommendations. CIKM 2023: 1158-1167 - [c1027]Xi Wu, Liangwei Yang, Jibing Gong, Chao Zhou, Tianyu Lin, Xiaolong Liu, Philip S. Yu:
Dimension Independent Mixup for Hard Negative Sample in Collaborative Filtering. CIKM 2023: 2785-2794 - [c1026]Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu:
Group Identification via Transitional Hypergraph Convolution with Cross-view Self-supervised Learning. CIKM 2023: 2969-2979 - [c1025]Liangwei Yang, Zhiwei Liu, Chen Wang, Mingdai Yang, Xiaolong Liu, Jing Ma, Philip S. Yu:
Graph-based Alignment and Uniformity for Recommendation. CIKM 2023: 4395-4399 - [c1024]Lin Meng, Xiaonan Zhang, Jiawei Zhang, Philip S. Yu:
Location-Adaptive Generative Graph Augmentation for Fraud Detection. CogMI 2023: 24-30 - [c1023]Mingxia Wang, Yun Xiong, Yao Zhang, Philip S. Yu, Yangyong Zhu:
Hierarchical Encoder-Decoder with Addressable Memory Network for Diagnosis Prediction. DASFAA (4) 2023: 266-275 - [c1022]Yahui Chai, Xiaobin Rui, Jie Yang, Philip S. Yu, Zhixiao Wang:
A Graph Embedding Approach for Link Prediction via Triadic Closure Based Direct Aggregation and Weighted Concatenation. DASFAA (3) 2023: 341-350 - [c1021]Zefeng Chen, Wensheng Gan, Gengsen Huang, Yanxin Zheng, Philip S. Yu:
Towards Contiguous Sequences in Uncertain Data. DSAA 2023: 1-10 - [c1020]Hoang Nguyen, Ye Liu, Chenwei Zhang, Tao Zhang, Philip S. Yu:
CoF-CoT: Enhancing Large Language Models with Coarse-to-Fine Chain-of-Thought Prompting for Multi-domain NLU Tasks. EMNLP 2023: 12109-12119 - [c1019]Yawen Yang, Xuming Hu, Fukun Ma, Shu'ang Li, Aiwei Liu, Lijie Wen, Philip S. Yu:
Gaussian Prior Reinforcement Learning for Nested Named Entity Recognition. ICASSP 2023: 1-5 - [c1018]Chin-Yuan Yeh, Hsi-Wen Chen, De-Nian Yang, Wang-Chien Lee, Philip S. Yu, Ming-Syan Chen:
Planning Data Poisoning Attacks on Heterogeneous Recommender Systems in a Multiplayer Setting. ICDE 2023: 2510-2523 - [c1017]Li Sun, Zhenhao Huang, Hua Wu, Junda Ye, Hao Peng, Zhengtao Yu, Philip S. Yu:
DeepRicci: Self-supervised Graph Structure-Feature Co-Refinement for Alleviating Over-squashing. ICDM 2023: 558-567 - [c1016]Guangjie Zeng, Hao Peng, Angsheng Li, Zhiwei Liu, Chunyang Liu, Philip S. Yu, Lifang He:
Unsupervised Skin Lesion Segmentation via Structural Entropy Minimization on Multi-Scale Superpixel Graphs. ICDM 2023: 768-777 - [c1015]Zheng Liu, Xiaohan Li, Philip S. Yu:
A Counterfactual Fair Model for Longitudinal Electronic Health Records via Deconfounder. ICDM 2023: 1175-1180 - [c1014]Ke Xu, Yuanjie Zhu, Weizhi Zhang, Philip S. Yu:
Graph Neural Ordinary Differential Equations-based method for Collaborative Filtering. ICDM 2023: 1445-1450 - [c1013]Shen Wang, Ziwei Fan, Jibing Gong, Xiaokai Wei, Philip S. Yu:
IGCN: Item Influence Enhanced Graph Convolution Networks for Recommendation of Cold-Start Items. ICDM (Workshops) 2023: 1516-1525 - [c1012]Fanlong Zeng, Wensheng Gan, Yongheng Wang, Philip S. Yu:
Distributed Training of Large Language Models. ICPADS 2023: 840-847 - [c1011]Li Sun, Feiyang Wang, Junda Ye, Hao Peng, Philip S. Yu:
CONGREGATE: Contrastive Graph Clustering in Curvature Spaces. IJCAI 2023: 2296-2305 - [c1010]Xianghua Zeng, Hao Peng, Angsheng Li, Chunyang Liu, Lifang He, Philip S. Yu:
Hierarchical State Abstraction based on Structural Information Principles. IJCAI 2023: 4549-4557 - [c1009]Wenting Zhao, Ye Liu, Yao Wan, Yibo Wang, Zhongfen Deng, Philip S. Yu:
Localize, Retrieve and Fuse: A Generalized Framework for Free-Form Question Answering over Tables. IJCNLP (Findings) 2023: 1-12 - [c1008]Yibo Wang, Wenting Zhao, Yao Wan, Zhongfen Deng, Philip S. Yu:
Named Entity Recognition via Machine Reading Comprehension: A Multi-Task Learning Approach. IJCNLP (Findings) 2023: 13-19 - [c1007]Jiangshu Du, Congying Xia, Wenpeng Yin, Tingting Liang, Philip S. Yu:
All Labels Together: Low-shot Intent Detection with an Efficient Label Semantic Encoding Paradigm. IJCNLP (2) 2023: 131-138 - [c1006]Yuefei Lyu, Xiaoyu Yang, Jiaxin Liu, Sihong Xie, Philip S. Yu, Xi Zhang:
Interpretable and Effective Reinforcement Learning for Attacking against Graph-based Rumor Detection. IJCNN 2023: 1-9 - [c1005]Siddharth Bhatia, Mohit Wadhwa, Kenji Kawaguchi, Neil Shah, Philip S. Yu, Bryan Hooi:
Sketch-Based Anomaly Detection in Streaming Graphs. KDD 2023: 93-104 - [c1004]Yu Wang, Zhengyang Wang, Hengrui Zhang, Qingyu Yin, Xianfeng Tang, Yinghan Wang, Danqing Zhang, Limeng Cui, Monica Xiao Cheng, Bing Yin, Suhang Wang, Philip S. Yu:
Exploiting Intent Evolution in E-commercial Query Recommendation. KDD 2023: 5162-5173 - [c1003]Chuishi Meng, Yanhua Li, Yu Zheng, Jieping Ye, Qiang Yang, Philip S. Yu, Ouri Wolfson:
The 12th International Workshop on Urban Computing. KDD 2023: 5874-5875 - [c1002]Xuming Hu, Junzhe Chen, Aiwei Liu, Shiao Meng, Lijie Wen, Philip S. Yu:
Prompt Me Up: Unleashing the Power of Alignments for Multimodal Entity and Relation Extraction. ACM Multimedia 2023: 5185-5194 - [c1001]Fangxin Wang, Lu Cheng, Ruocheng Guo, Kay Liu, Philip S. Yu:
Equal Opportunity of Coverage in Fair Regression. NeurIPS 2023 - [c1000]Yuwei Cao, Liangwei Yang, Chen Wang, Zhiwei Liu, Hao Peng, Chenyu You, Philip S. Yu:
Multi-task Item-attribute Graph Pre-training for Strict Cold-start Item Recommendation. RecSys 2023: 322-333 - [c999]Jia-Hao Syu, Jerry Chun-Wei Lin, Philip S. Yu:
Anomaly Detection Networks and Fuzzy Control Modules for Energy Grid Management with Q-Learning-Based Decision Making. SDM 2023: 397-405 - [c998]Hoang H. Nguyen, Chenwei Zhang, Ye Liu, Philip S. Yu:
Slot Induction via Pre-trained Language Model Probing and Multi-level Contrastive Learning. SIGDIAL 2023: 470-481 - [c997]Yibo Wang, Yanbing Xue, Bo Liu, Musen Wen, Wenting Zhao, Stephen D. Guo, Philip S. Yu:
Click-Conversion Multi-Task Model with Position Bias Mitigation for Sponsored Search in eCommerce. SIGIR 2023: 1884-1888 - [c996]Ziwei Fan, Ke Xu, Zhang Dong, Hao Peng, Jiawei Zhang, Philip S. Yu:
Graph Collaborative Signals Denoising and Augmentation for Recommendation. SIGIR 2023: 2037-2041 - [c995]Xuming Hu, Zhaochen Hong, Zhijiang Guo, Lijie Wen, Philip S. Yu:
Read it Twice: Towards Faithfully Interpretable Fact Verification by Revisiting Evidence. SIGIR 2023: 2319-2323 - [c994]Xuming Hu, Junzhe Chen, Shiao Meng, Lijie Wen, Philip S. Yu:
SelfLRE: Self-refining Representation Learning for Low-resource Relation Extraction. SIGIR 2023: 2364-2368 - [c993]Xuming Hu, Zhaochen Hong, Chenwei Zhang, Irwin King, Philip S. Yu:
Think Rationally about What You See: Continuous Rationale Extraction for Relation Extraction. SIGIR 2023: 2436-2440 - [c992]Xuming Hu, Zhijiang Guo, Junzhe Chen, Lijie Wen, Philip S. Yu:
MR2: A Benchmark for Multimodal Retrieval-Augmented Rumor Detection in Social Media. SIGIR 2023: 2901-2912 - [c991]Liangwei Yang, Shengjie Wang, Yunzhe Tao, Jiankai Sun, Xiaolong Liu, Philip S. Yu, Taiqing Wang:
DGRec: Graph Neural Network for Recommendation with Diversified Embedding Generation. WSDM 2023: 661-669 - [c990]Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu:
Ranking-based Group Identification via Factorized Attention on Social Tripartite Graph. WSDM 2023: 769-777 - [c989]Xiaosu Wang, Yun Xiong, Beichen Kang, Yao Zhang, Philip S. Yu, Yangyong Zhu:
Reducing Negative Effects of the Biases of Language Models in Zero-Shot Setting. WSDM 2023: 904-912 - [c988]Cheng Ji, Jianxin Li, Hao Peng, Jia Wu, Xingcheng Fu, Qingyun Sun, Philip S. Yu:
Unbiased and Efficient Self-Supervised Incremental Contrastive Learning. WSDM 2023: 922-930 - [c987]Xixi Wu, Yun Xiong, Yao Zhang, Yizhu Jiao, Jiawei Zhang, Yangyong Zhu, Philip S. Yu:
ConsRec: Learning Consensus Behind Interactions for Group Recommendation. WWW 2023: 240-250 - [c986]Cheng Yang, Xumeng Gong, Chuan Shi, Philip S. Yu:
A Post-Training Framework for Improving Heterogeneous Graph Neural Networks. WWW 2023: 251-262 - [c985]Dongcheng Zou, Hao Peng, Xiang Huang, Renyu Yang, Jianxin Li, Jia Wu, Chunyang Liu, Philip S. Yu:
SE-GSL: A General and Effective Graph Structure Learning Framework through Structural Entropy Optimization. WWW 2023: 499-510 - [c984]Hsi-Wen Chen, De-Nian Yang, Wang-Chien Lee, Philip S. Yu, Ming-Syan Chen:
CMINet: a Graph Learning Framework for Content-aware Multi-channel Influence Diffusion. WWW 2023: 545-555 - [c983]Wensheng Gan, Zhenqiang Ye, Shicheng Wan, Philip S. Yu:
Web 3.0: The Future of Internet. WWW (Companion Volume) 2023: 1266-1275 - [c982]Ziwei Fan, Zhiwei Liu, Hao Peng, Philip S. Yu:
Mutual Wasserstein Discrepancy Minimization for Sequential Recommendation. WWW 2023: 1375-1385 - [c981]Haoran Wang, Yingtong Dou, Canyu Chen, Lichao Sun, Philip S. Yu, Kai Shu:
Attacking Fake News Detectors via Manipulating News Social Engagement. WWW 2023: 3978-3986 - [c980]Jing Ma, Liangwei Yang, Qiong Feng, Weizhi Zhang, Philip S. Yu:
Graph-based Village Level Poverty Identification. WWW 2023: 4115-4119 - [i447]Qingyun Sun, Jianxin Li, Beining Yang, Xingcheng Fu, Hao Peng, Philip S. Yu:
Self-organization Preserved Graph Structure Learning with Principle of Relevant Information. CoRR abs/2301.00015 (2023) - [i446]Xiaohan Li, Yuqing Liu, Zheng Liu, Philip S. Yu:
Time-aware Hyperbolic Graph Attention Network for Session-based Recommendation. CoRR abs/2301.03780 (2023) - [i445]Lilin Zhang, Ning Yang, Yanchao Sun, Philip S. Yu:
Provable Unrestricted Adversarial Training without Compromise with Generalizability. CoRR abs/2301.09069 (2023) - [i444]Cheng Ji, Jianxin Li, Hao Peng, Jia Wu, Xingcheng Fu, Qingyun Sun, Philip S. Yu:
Unbiased and Efficient Self-Supervised Incremental Contrastive Learning. CoRR abs/2301.12104 (2023) - [i443]Ziwei Fan, Zhiwei Liu, Hao Peng, Philip S. Yu:
Mutual Wasserstein Discrepancy Minimization for Sequential Recommendation. CoRR abs/2301.12197 (2023) - [i442]Hengrui Zhang, Shen Wang, Vassilis N. Ioannidis, Soji Adeshina, Jiani Zhang, Xiao Qin, Christos Faloutsos, Da Zheng, George Karypis, Philip S. Yu:
OrthoReg: Improving Graph-regularized MLPs via Orthogonality Regularization. CoRR abs/2302.00109 (2023) - [i441]Xixi Wu, Yun Xiong, Yao Zhang, Yizhu Jiao, Jiawei Zhang, Yangyong Zhu, Philip S. Yu:
ConsRec: Learning Consensus Behind Interactions for Group Recommendation. CoRR abs/2302.03555 (2023) - [i440]Minqi Jiang, Chaochuan Hou, Ao Zheng, Xiyang Hu, Songqiao Han, Hailiang Huang, Xiangnan He, Philip S. Yu, Yue Zhao:
Weakly Supervised Anomaly Detection: A Survey. CoRR abs/2302.04549 (2023) - [i439]Jing Ma, Liangwei Yang, Qiong Feng, Weizhi Zhang, Philip S. Yu:
Graph-based Village Level Poverty Identification. CoRR abs/2302.06862 (2023) - [i438]Haoran Wang, Yingtong Dou, Canyu Chen, Lichao Sun, Philip S. Yu, Kai Shu:
Attacking Fake News Detectors via Manipulating News Social Engagement. CoRR abs/2302.07363 (2023) - [i437]Ce Zhou, Qian Li, Chen Li, Jun Yu, Yixin Liu, Guangjing Wang, Kai Zhang, Cheng Ji, Qiben Yan, Lifang He, Hao Peng, Jianxin Li, Jia Wu, Ziwei Liu, Pengtao Xie, Caiming Xiong, Jian Pei, Philip S. Yu, Lichao Sun:
A Comprehensive Survey on Pretrained Foundation Models: A History from BERT to ChatGPT. CoRR abs/2302.09419 (2023) - [i436]Yihan Cao, Siyu Li, Yixin Liu, Zhiling Yan, Yutong Dai, Philip S. Yu, Lichao Sun:
A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT. CoRR abs/2303.04226 (2023) - [i435]Dongcheng Zou, Hao Peng, Xiang Huang, Renyu Yang, Jianxin Li, Jia Wu, Chunyang Liu, Philip S. Yu:
SE-GSL: A General and Effective Graph Structure Learning Framework through Structural Entropy Optimization. CoRR abs/2303.09778 (2023) - [i434]Aiwei Liu, Xuming Hu, Lijie Wen, Philip S. Yu:
A comprehensive evaluation of ChatGPT's zero-shot Text-to-SQL capability. CoRR abs/2303.13547 (2023) - [i433]Cheng Yang, Xumeng Gong, Chuan Shi, Philip S. Yu:
A Post-Training Framework for Improving Heterogeneous Graph Neural Networks. CoRR abs/2304.00698 (2023) - [i432]Yao Chen, Wensheng Gan, Gengsen Huang, Yongdong Wu, Philip S. Yu:
Privacy-Preserving Federated Discovery of DNA Motifs with Differential Privacy. CoRR abs/2304.01689 (2023) - [i431]Ziwei Fan, Ke Xu, Zhang Dong, Hao Peng, Jiawei Zhang, Philip S. Yu:
Graph Collaborative Signals Denoising and Augmentation for Recommendation. CoRR abs/2304.03344 (2023) - [i430]Wensheng Gan, Zhenqiang Ye, Shicheng Wan, Philip S. Yu:
Web 3.0: The Future of Internet. CoRR abs/2304.06032 (2023) - [i429]Shicheng Wan, Hong Lin, Wensheng Gan, Jiahui Chen, Philip S. Yu:
Web3: The Next Internet Revolution. CoRR abs/2304.06111 (2023) - [i428]Yu Wang, Zhiwei Liu, Liangwei Yang, Philip S. Yu:
Conditional Denoising Diffusion for Sequential Recommendation. CoRR abs/2304.11433 (2023) - [i427]Xianghua Zeng, Hao Peng, Angsheng Li, Chunyang Liu, Lifang He, Philip S. Yu:
Hierarchical State Abstraction Based on Structural Information Principles. CoRR abs/2304.12000 (2023) - [i426]Zefeng Chen, Wensheng Gan, Jiayi Sun, Jiayang Wu, Philip S. Yu:
Open Metaverse: Issues, Evolution, and Future. CoRR abs/2304.13931 (2023) - [i425]Xuming Hu, Zhaochen Hong, Chenwei Zhang, Irwin King, Philip S. Yu:
Think Rationally about What You See: Continuous Rationale Extraction for Relation Extraction. CoRR abs/2305.03503 (2023) - [i424]Xuming Hu, Zhaochen Hong, Zhijiang Guo, Lijie Wen, Philip S. Yu:
Read it Twice: Towards Faithfully Interpretable Fact Verification by Revisiting Evidence. CoRR abs/2305.03507 (2023) - [i423]Li Sun, Feiyang Wang, Junda Ye, Hao Peng, Philip S. Yu:
Contrastive Graph Clustering in Curvature Spaces. CoRR abs/2305.03555 (2023) - [i422]Yawen Yang, Xuming Hu, Fukun Ma, Shu'ang Li, Aiwei Liu, Lijie Wen, Philip S. Yu:
Gaussian Prior Reinforcement Learning for Nested Named Entity Recognition. CoRR abs/2305.07266 (2023) - [i421]Ziwei Fan, Zhiwei Liu, Shelby Heinecke, Jianguo Zhang, Huan Wang, Caiming Xiong, Philip S. Yu:
Zero-shot Item-based Recommendation via Multi-task Product Knowledge Graph Pre-Training. CoRR abs/2305.07633 (2023) - [i420]Shuang Li, Xuming Hu, Aiwei Liu, Yawen Yang, Fukun Ma, Philip S. Yu, Lijie Wen:
Enhancing Cross-lingual Natural Language Inference by Soft Prompting with Multilingual Verbalizer. CoRR abs/2305.12761 (2023) - [i419]Xuming Hu, Zhijiang Guo, Guanyu Wu, Lijie Wen, Philip S. Yu:
Give Me More Details: Improving Fact-Checking with Latent Retrieval. CoRR abs/2305.16128 (2023) - [i418]Xuming Hu, Zhijiang Guo, Zhiyang Teng, Irwin King, Philip S. Yu:
Multimodal Relation Extraction with Cross-Modal Retrieval and Synthesis. CoRR abs/2305.16166 (2023) - [i417]Xuming Hu, Aiwei Liu, Zeqi Tan, Xin Zhang, Chenwei Zhang, Irwin King, Philip S. Yu:
GDA: Generative Data Augmentation Techniques for Relation Extraction Tasks. CoRR abs/2305.16663 (2023) - [i416]Liangqi Yuan, Lichao Sun, Philip S. Yu, Ziran Wang:
Decentralized Federated Learning: A Survey and Perspective. CoRR abs/2306.01603 (2023) - [i415]Mengzhu Sun, Xi Zhang, Jianqiang Ma, Sihong Xie, Yazheng Liu, Philip S. Yu:
Inconsistent Matters: A Knowledge-guided Dual-consistency Network for Multi-modal Rumor Detection. CoRR abs/2306.02137 (2023) - [i414]Heng Xu, Tianqing Zhu, Lefeng Zhang, Wanlei Zhou, Philip S. Yu:
Machine Unlearning: A Survey. CoRR abs/2306.03558 (2023) - [i413]Xuan Lin, Lichang Dai, Yafang Zhou, Zu-Guo Yu, Wen Zhang, Jian-Yu Shi, Dong-Sheng Cao, Li Zeng, Haowen Chen, Bosheng Song, Philip S. Yu, Xiangxiang Zeng:
Comprehensive evaluation of deep and graph learning on drug-drug interactions prediction. CoRR abs/2306.05257 (2023) - [i412]Zefeng Chen, Wensheng Gan, Gengsen Huang, Zhenlian Qi, Yan Li, Philip S. Yu:
TALENT: Targeted Mining of Non-overlapping Sequential Patterns. CoRR abs/2306.06470 (2023) - [i411]Yue Huang, Qihui Zhang, Philip S. Yu, Lichao Sun:
TrustGPT: A Benchmark for Trustworthy and Responsible Large Language Models. CoRR abs/2306.11507 (2023) - [i410]Ziwei Fan, Zhiwei Liu, Hao Peng, Philip S. Yu:
Addressing the Rank Degeneration in Sequential Recommendation via Singular Spectrum Smoothing. CoRR abs/2306.11986 (2023) - [i409]Huiqiang Chen, Tianqing Zhu, Tao Zhang, Wanlei Zhou, Philip S. Yu:
Privacy and Fairness in Federated Learning: on the Perspective of Trade-off. CoRR abs/2306.14123 (2023) - [i408]Yuwei Cao, Liangwei Yang, Chen Wang, Zhiwei Liu, Hao Peng, Chenyu You, Philip S. Yu:
Multi-task Item-attribute Graph Pre-training for Strict Cold-start Item Recommendation. CoRR abs/2306.14462 (2023) - [i407]Xi Wu, Liangwei Yang, Jibing Gong, Chao Zhou, Tianyu Lin, Xiaolong Liu, Philip S. Yu:
Dimension Independent Mixup for Hard Negative Sample in Collaborative Filtering. CoRR abs/2306.15905 (2023) - [i406]Yupeng Chang, Xu Wang, Jindong Wang, Yuan Wu, Kaijie Zhu, Hao Chen, Linyi Yang, Xiaoyuan Yi, Cunxiang Wang, Yidong Wang, Wei Ye, Yue Zhang, Yi Chang, Philip S. Yu, Qiang Yang, Xing Xie:
A Survey on Evaluation of Large Language Models. CoRR abs/2307.03109 (2023) - [i405]Hoang Nguyen, Chenwei Zhang, Tao Zhang, Eugene Rohrbaugh, Philip S. Yu:
Enhancing Cross-lingual Transfer via Phonemic Transcription Integration. CoRR abs/2307.04361 (2023) - [i404]Yibo Wang, Yanbing Xue, Bo Liu, Musen Wen, Wenting Zhao, Stephen D. Guo, Philip S. Yu:
Click-Conversion Multi-Task Model with Position Bias Mitigation for Sponsored Search in eCommerce. CoRR abs/2307.16060 (2023) - [i403]Aiwei Liu, Leyi Pan, Xuming Hu, Shu'ang Li, Lijie Wen, Irwin King, Philip S. Yu:
A Private Watermark for Large Language Models. CoRR abs/2307.16230 (2023) - [i402]Hoang H. Nguyen, Chenwei Zhang, Ye Liu, Philip S. Yu:
Slot Induction via Pre-trained Language Model Probing and Multi-level Contrastive Learning. CoRR abs/2308.04712 (2023) - [i401]Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu:
Group Identification via Transitional Hypergraph Convolution with Cross-view Self-supervised Learning. CoRR abs/2308.08620 (2023) - [i400]Liangwei Yang, Zhiwei Liu, Chen Wang, Mingdai Yang, Xiaolong Liu, Jing Ma, Philip S. Yu:
Graph-based Alignment and Uniformity for Recommendation. CoRR abs/2308.09292 (2023) - [i399]Zheng Liu, Xiaohan Li, Philip S. Yu:
Mitigating Health Disparity on Biased Electronic Health Records via Deconfounder. CoRR abs/2308.11819 (2023) - [i398]Junling Liu, Chao Liu, Peilin Zhou, Qichen Ye, Dading Chong, Kang Zhou, Yueqi Xie, Yuwei Cao, Shoujin Wang, Chenyu You, Philip S. Yu:
LLMRec: Benchmarking Large Language Models on Recommendation Task. CoRR abs/2308.12241 (2023) - [i397]Yi Zhang, Yuying Zhao, Zhaoqing Li, Xueqi Cheng, Yu Wang, Olivera Kotevska, Philip S. Yu, Tyler Derr:
A Survey on Privacy in Graph Neural Networks: Attacks, Preservation, and Applications. CoRR abs/2308.16375 (2023) - [i396]Guangjie Zeng, Hao Peng, Angsheng Li, Zhiwei Liu, Chunyang Liu, Philip S. Yu, Lifang He:
Unsupervised Skin Lesion Segmentation via Structural Entropy Minimization on Multi-Scale Superpixel Graphs. CoRR abs/2309.01899 (2023) - [i395]Jiangshu Du, Congying Xia, Wenpeng Yin, Tingting Liang, Philip S. Yu:
All Labels Together: Low-shot Intent Detection with an Efficient Label Semantic Encoding Paradigm. CoRR abs/2309.03563 (2023) - [i394]Yibo Wang, Wenting Zhao, Yao Wan, Zhongfen Deng, Philip S. Yu:
Named Entity Recognition via Machine Reading Comprehension: A Multi-Task Learning Approach. CoRR abs/2309.11027 (2023) - [i393]Wenting Zhao, Ye Liu, Yao Wan, Yibo Wang, Zhongfen Deng, Philip S. Yu:
Localize, Retrieve and Fuse: A Generalized Framework for Free-Form Question Answering over Tables. CoRR abs/2309.11049 (2023) - [i392]Zheng Wang, Hongming Ding, Li Pan, Jianhua Li, Zhiguo Gong, Philip S. Yu:
From Cluster Assumption to Graph Convolution: Graph-based Semi-Supervised Learning Revisited. CoRR abs/2309.13599 (2023) - [i391]Chunkai Zhang, Maohua Lyu, Huaijin Hao, Wensheng Gan, Philip S. Yu:
Discovering Utility-driven Interval Rules. CoRR abs/2309.16102 (2023) - [i390]Xuming Hu, Junzhe Chen, Xiaochuan Li, Yufei Guo, Lijie Wen, Philip S. Yu, Zhijiang Guo:
Do Large Language Models Know about Facts? CoRR abs/2310.05177 (2023) - [i389]Zhongfen Deng, Wei-Te Chen, Lei Chen, Philip S. Yu:
AE-smnsMLC: Multi-Label Classification with Semantic Matching and Negative Label Sampling for Product Attribute Value Extraction. CoRR abs/2310.07137 (2023) - [i388]Chen Wang, Liangwei Yang, Zhiwei Liu, Xiaolong Liu, Mingdai Yang, Yueqing Liang, Philip S. Yu:
Collaborative Contextualization: Bridging the Gap between Collaborative Filtering and Pre-trained Language Model. CoRR abs/2310.09400 (2023) - [i387]Jiawei Liu, Cheng Yang, Zhiyuan Lu, Junze Chen, Yibo Li, Mengmei Zhang, Ting Bai, Yuan Fang, Lichao Sun, Philip S. Yu, Chuan Shi:
Towards Graph Foundation Models: A Survey and Beyond. CoRR abs/2310.11829 (2023) - [i386]Xiaolong Liu, Liangwei Yang, Zhiwei Liu, Mingdai Yang, Chen Wang, Hao Peng, Philip S. Yu:
Knowledge Graph Context-Enhanced Diversified Recommendation. CoRR abs/2310.13253 (2023) - [i385]Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu:
Unified Pretraining for Recommendation via Task Hypergraphs. CoRR abs/2310.13286 (2023) - [i384]Hong Lin, Zirun Gan, Wensheng Gan, Zhenlian Qi, Yuehua Wang, Philip S. Yu:
Interaction in Metaverse: A Survey. CoRR abs/2310.13699 (2023) - [i383]Hoang H. Nguyen, Ye Liu, Chenwei Zhang, Tao Zhang, Philip S. Yu:
CoF-CoT: Enhancing Large Language Models with Coarse-to-Fine Chain-of-Thought Prompting for Multi-domain NLU Tasks. CoRR abs/2310.14623 (2023) - [i382]Xuming Hu, Junzhe Chen, Aiwei Liu, Shiao Meng, Lijie Wen, Philip S. Yu:
Prompt Me Up: Unleashing the Power of Alignments for Multimodal Entity and Relation Extraction. CoRR abs/2310.16822 (2023) - [i381]Jiaqian Ren, Hao Peng, Lei Jiang, Zhiwei Liu, Jia Wu, Zhengtao Yu, Philip S. Yu:
Uncertainty-guided Boundary Learning for Imbalanced Social Event Detection. CoRR abs/2310.19247 (2023) - [i380]Wenting Zhao, Ye Liu, Tong Niu, Yao Wan, Philip S. Yu, Shafiq Joty, Yingbo Zhou, Semih Yavuz:
DIVKNOWQA: Assessing the Reasoning Ability of LLMs via Open-Domain Question Answering over Knowledge Base and Text. CoRR abs/2310.20170 (2023) - [i379]Xiangjue Dong, Yibo Wang, Philip S. Yu, James Caverlee:
Probing Explicit and Implicit Gender Bias through LLM Conditional Text Generation. CoRR abs/2311.00306 (2023) - [i378]Jiangnan Xia, Yu Yang, Senzhang Wang, Hongzhi Yin, Jiannong Cao, Philip S. Yu:
Bayes-enhanced Multi-view Attention Networks for Robust POI Recommendation. CoRR abs/2311.00491 (2023) - [i377]Hao Niu, Yun Xiong, Xiaosu Wang, Philip S. Yu:
Joint Learning of Local and Global Features for Aspect-based Sentiment Classification. CoRR abs/2311.01030 (2023) - [i376]Fangxin Wang, Lu Cheng, Ruocheng Guo, Kay Liu, Philip S. Yu:
Equal Opportunity of Coverage in Fair Regression. CoRR abs/2311.02243 (2023) - [i375]Zhongfen Deng, Hao Peng, Tao Zhang, Shuaiqi Liu, Wenting Zhao, Yibo Wang, Philip S. Yu:
JPAVE: A Generation and Classification-based Model for Joint Product Attribute Prediction and Value Extraction. CoRR abs/2311.04196 (2023) - [i374]Zhongfen Deng, Seunghyun Yoon, Trung Bui, Franck Dernoncourt, Quan Hung Tran, Shuaiqi Liu, Wenting Zhao, Tao Zhang, Yibo Wang, Philip S. Yu:
Aspect-based Meeting Transcript Summarization: A Two-Stage Approach with Weak Supervision on Sentence Classification. CoRR abs/2311.04292 (2023) - [i373]Xusheng Zhao, Hao Peng, Qiong Dai, Xu Bai, Huailiang Peng, Yanbing Liu, Qinglang Guo, Philip S. Yu:
RDGCN: Reinforced Dependency Graph Convolutional Network for Aspect-based Sentiment Analysis. CoRR abs/2311.04467 (2023) - [i372]Wensheng Gan, Shicheng Wan, Philip S. Yu:
Model-as-a-Service (MaaS): A Survey. CoRR abs/2311.05804 (2023) - [i371]Fanlong Zeng, Wensheng Gan, Yongheng Wang, Ning Liu, Philip S. Yu:
Large Language Models for Robotics: A Survey. CoRR abs/2311.07226 (2023) - [i370]Yibo Wang, Xiangjue Dong, James Caverlee, Philip S. Yu:
DALA: A Distribution-Aware LoRA-Based Adversarial Attack against Pre-trained Language Models. CoRR abs/2311.08598 (2023) - [i369]Xiaolong Liu, Liangwei Yang, Zhiwei Liu, Xiaohan Li, Mingdai Yang, Chen Wang, Philip S. Yu:
Group-Aware Interest Disentangled Dual-Training for Personalized Recommendation. CoRR abs/2311.09577 (2023) - [i368]Xiaolong Liu, Liangwei Yang, Chen Wang, Mingdai Yang, Zhiwei Liu, Philip S. Yu:
Multi-view Graph Convolution for Participant Recommendation. CoRR abs/2311.12136 (2023) - [i367]Ke Xu, Yuanjie Zhu, Weizhi Zhang, Philip S. Yu:
Graph Neural Ordinary Differential Equations-based method for Collaborative Filtering. CoRR abs/2311.12329 (2023) - [i366]Jiayang Wu, Wensheng Gan, Zefeng Chen, Shicheng Wan, Philip S. Yu:
Multimodal Large Language Models: A Survey. CoRR abs/2311.13165 (2023) - [i365]Jinqi Lai, Wensheng Gan, Jiayang Wu, Zhenlian Qi, Philip S. Yu:
Large Language Models in Law: A Survey. CoRR abs/2312.03718 (2023) - [i364]Aiwei Liu, Leyi Pan, Yijian Lu, Jingjing Li, Xuming Hu, Lijie Wen, Irwin King, Philip S. Yu:
A Survey of Text Watermarking in the Era of Large Language Models. CoRR abs/2312.07913 (2023) - [i363]Wenting Zhao, Ye Liu, Yao Wan, Yibo Wang, Qingyang Wu, Zhongfen Deng, Jiangshu Du, Shuaiqi Liu, Yunlong Xu, Philip S. Yu:
kNN-ICL: Compositional Task-Oriented Parsing Generalization with Nearest Neighbor In-Context Learning. CoRR abs/2312.10771 (2023) - [i362]Wei-Yao Wang, Wen-Chih Peng, Wei Wang, Philip S. Yu:
ShuttleSHAP: A Turn-Based Feature Attribution Approach for Analyzing Forecasting Models in Badminton. CoRR abs/2312.10942 (2023) - [i361]Kun Peng, Lei Jiang, Hao Peng, Rui Liu, Zhengtao Yu, Jiaqian Ren, Zhifeng Hao, Philip S. Yu:
Prompt Based Tri-Channel Graph Convolution Neural Network for Aspect Sentiment Triplet Extraction. CoRR abs/2312.11152 (2023) - [i360]Yu Wang, Zhiwei Liu, Jianguo Zhang, Weiran Yao, Shelby Heinecke, Philip S. Yu:
DRDT: Dynamic Reflection with Divergent Thinking for LLM-based Sequential Recommendation. CoRR abs/2312.11336 (2023) - [i359]Yuwei Cao, Hao Peng, Zhengtao Yu, Philip S. Yu:
Hierarchical and Incremental Structural Entropy Minimization for Unsupervised Social Event Detection. CoRR abs/2312.11891 (2023) - [i358]Zi-Feng Mai, Chang-Dong Wang, Zhongjie Zeng, Ya Li, Jiaquan Chen, Philip S. Yu:
Hypergraph Enhanced Knowledge Tree Prompt Learning for Next-Basket Recommendation. CoRR abs/2312.15851 (2023) - [i357]Kay Liu, Hengrui Zhang, Ziqing Hu, Fangxin Wang, Philip S. Yu:
Data Augmentation for Supervised Graph Outlier Detection with Latent Diffusion Models. CoRR abs/2312.17679 (2023) - 2022
- [b5]Chuan Shi, Xiao Wang, Philip S. Yu:
Heterogeneous Graph Representation Learning and Applications. Artificial Intelligence: Foundations, Theory, and Algorithms, Springer 2022, ISBN 978-981-16-6165-5, pp. 1-318 - [j458]Mohammed A. Fouad, Wedad Hussein, Sherine Rady, Philip S. Yu, Tarek F. Gharib:
An Efficient Approach for Mining Reliable High Utility Patterns. IEEE Access 10: 1419-1431 (2022) - [j457]Mohammed A. Fouad, Wedad Hussein, Sherine Rady, Philip S. Yu, Tarek F. Gharib:
An Efficient Approach for Rational Next-Basket Recommendation. IEEE Access 10: 75657-75671 (2022) - [j456]Jiawei Liu, Chuan Shi, Cheng Yang, Zhiyuan Lu, Philip S. Yu:
A survey on heterogeneous information network based recommender systems: Concepts, methods, applications and resources. AI Open 3: 40-57 (2022) - [j455]Lefeng Zhang, Tianqing Zhu, Ping Xiong, Wanlei Zhou, Philip S. Yu:
More than Privacy: Adopting Differential Privacy in Game-theoretic Mechanism Design. ACM Comput. Surv. 54(7): 136:1-136:37 (2022) - [j454]Jianguo Chen, Kenli Li, Zhaolei Zhang, Keqin Li, Philip S. Yu:
A Survey on Applications of Artificial Intelligence in Fighting Against COVID-19. ACM Comput. Surv. 54(8): 158:1-158:32 (2022) - [j453]Hongsheng Hu, Zoran Salcic, Lichao Sun, Gillian Dobbie, Philip S. Yu, Xuyun Zhang:
Membership Inference Attacks on Machine Learning: A Survey. ACM Comput. Surv. 54(11s): 235:1-235:37 (2022) - [j452]Shirui Pan, Shaoxiong Ji, Di Jin, Feng Xia, Philip S. Yu:
Guest Editorial: Graph-powered machine learning in future-generation computing systems. Future Gener. Comput. Syst. 126: 88-90 (2022) - [j451]Zishuo Cheng, Dayong Ye, Tianqing Zhu, Wanlei Zhou, Philip S. Yu, Congcong Zhu:
Multi-agent reinforcement learning via knowledge transfer with differentially private noise. Int. J. Intell. Syst. 37(1): 799-828 (2022) - [j450]Shuai Gao, Zhongbao Zhang, Sen Su, Philip S. Yu:
REBORN: Transfer learning based social network alignment. Inf. Sci. 589: 265-282 (2022) - [j449]Boyan Wang, Xuegang Hu, Chenwei Zhang, Pei-Pei Li, Philip S. Yu:
Hierarchical GAN-Tree and Bi-Directional Capsules for multi-label image classification. Knowl. Based Syst. 238: 107882 (2022) - [j448]Rui Wang, Ning Yang, Philip S. Yu:
Learning aspect-level complementarity for intent-aware complementary recommendation. Knowl. Based Syst. 258: 109936 (2022) - [j447]Xusheng Zhao, Jia Wu, Hao Peng, Amin Beheshti, Jessica J. M. Monaghan, David McAlpine, Heivet Hernandez-Perez, Mark Dras, Qiong Dai, Yangyang Li, Philip S. Yu, Lifang He:
Deep reinforcement learning guided graph neural networks for brain network analysis. Neural Networks 154: 56-67 (2022) - [j446]Zhiyu Yao, Yunbo Wang, Jianmin Wang, Philip S. Yu, Mingsheng Long:
VideoDG: Generalizing Temporal Relations in Videos to Novel Domains. IEEE Trans. Pattern Anal. Mach. Intell. 44(11): 7989-8004 (2022) - [j445]Yizhou Sun, Jiawei Han, Xifeng Yan, Philip S. Yu, Tianyi Wu:
Heterogeneous Information Networks: the Past, the Present, and the Future. Proc. VLDB Endow. 15(12): 3807-3811 (2022) - [j444]Qian Li, Hao Peng, Jianxin Li, Jia Wu, Yuanxing Ning, Lihong Wang, Philip S. Yu, Zheng Wang:
Reinforcement Learning-Based Dialogue Guided Event Extraction to Exploit Argument Relations. IEEE ACM Trans. Audio Speech Lang. Process. 30: 520-533 (2022) - [j443]Qianren Mao, Jianxin Li, Chenghua Lin, Congwen Chen, Hao Peng, Lihong Wang, Philip S. Yu:
Adaptive Pre-Training and Collaborative Fine-Tuning: A Win-Win Strategy to Improve Review Analysis Tasks. IEEE ACM Trans. Audio Speech Lang. Process. 30: 622-634 (2022) - [j442]Qianren Mao, Jianxin Li, Hao Peng, Shizhu He, Lihong Wang, Philip S. Yu, Zheng Wang:
Fact-Driven Abstractive Summarization by Utilizing Multi-Granular Multi-Relational Knowledge. IEEE ACM Trans. Audio Speech Lang. Process. 30: 1665-1678 (2022) - [j441]Di Jin, Wenjun Wang, Guojie Song, Philip S. Yu, Jiawei Han:
Guest Editorial: Special Issue on Network Structural Modeling and Learning in Big Data. IEEE Trans. Big Data 8(4): 867-868 (2022) - [j440]Hao Peng, Renyu Yang, Zheng Wang, Jianxin Li, Lifang He, Philip S. Yu, Albert Y. Zomaya, Rajiv Ranjan:
Lime: Low-Cost and Incremental Learning for Dynamic Heterogeneous Information Networks. IEEE Trans. Computers 71(3): 628-642 (2022) - [j439]Jie Xu, Zhoujun Li, Feiran Huang, Chaozhuo Li, Philip S. Yu:
Visual Sentiment Analysis With Social Relations-Guided Multiattention Networks. IEEE Trans. Cybern. 52(6): 4472-4484 (2022) - [j438]Shi-Ting Zhong, Ling Huang, Chang-Dong Wang, Jian-Huang Lai, Philip S. Yu:
An Autoencoder Framework With Attention Mechanism for Cross-Domain Recommendation. IEEE Trans. Cybern. 52(6): 5229-5241 (2022) - [j437]Dayong Ye, Tianqing Zhu, Zishuo Cheng, Wanlei Zhou, Philip S. Yu:
Differential Advising in Multiagent Reinforcement Learning. IEEE Trans. Cybern. 52(6): 5508-5521 (2022) - [j436]Chang-Dong Wang, Wei Shi, Ling Huang, Kun-Yu Lin, Dong Huang, Philip S. Yu:
Node Pair Information Preserving Network Embedding Based on Adversarial Networks. IEEE Trans. Cybern. 52(7): 5908-5922 (2022) - [j435]Man-Sheng Chen, Ling Huang, Chang-Dong Wang, Dong Huang, Philip S. Yu:
Multiview Subspace Clustering With Grouping Effect. IEEE Trans. Cybern. 52(8): 7655-7668 (2022) - [j434]Tie Li, Gang Kou, Yi Peng, Philip S. Yu:
An Integrated Cluster Detection, Optimization, and Interpretation Approach for Financial Data. IEEE Trans. Cybern. 52(12): 13848-13861 (2022) - [j433]Dayong Ye, Tianqing Zhu, Sheng Shen, Wanlei Zhou, Philip S. Yu:
Differentially Private Multi-Agent Planning for Logistic-Like Problems. IEEE Trans. Dependable Secur. Comput. 19(2): 1212-1226 (2022) - [j432]Qian Li, Hao Peng, Jianxin Li, Congying Xia, Renyu Yang, Lichao Sun, Philip S. Yu, Lifang He:
A Survey on Text Classification: From Traditional to Deep Learning. ACM Trans. Intell. Syst. Technol. 13(2): 31:1-31:41 (2022) - [j431]Senzhang Wang, Meiyue Zhang, Hao Miao, Zhaohui Peng, Philip S. Yu:
Multivariate Correlation-aware Spatio-temporal Graph Convolutional Networks for Multi-scale Traffic Prediction. ACM Trans. Intell. Syst. Technol. 13(3): 38:1-38:22 (2022) - [j430]Zhiwei Liu, Liangwei Yang, Ziwei Fan, Hao Peng, Philip S. Yu:
Federated Social Recommendation with Graph Neural Network. ACM Trans. Intell. Syst. Technol. 13(4): 55:1-55:24 (2022) - [j429]Jianguo Chen, Kenli Li, Philip S. Yu:
Privacy-Preserving Deep Learning Model for Decentralized VANETs Using Fully Homomorphic Encryption and Blockchain. IEEE Trans. Intell. Transp. Syst. 23(8): 11633-11642 (2022) - [j428]Chunkai Zhang, Zilin Du, Yuting Yang, Wensheng Gan, Philip S. Yu:
On-Shelf Utility Mining of Sequence Data. ACM Trans. Knowl. Discov. Data 16(2): 21:1-21:31 (2022) - [j427]Jerry Chun-Wei Lin, Youcef Djenouri, Gautam Srivastava, Yuanfa Li, Philip S. Yu:
Scalable Mining of High-Utility Sequential Patterns With Three-Tier MapReduce Model. ACM Trans. Knowl. Discov. Data 16(3): 60:1-60:26 (2022) - [j426]Yali Gao, Xiaoyong Li, Hao Peng, Binxing Fang, Philip S. Yu:
HinCTI: A Cyber Threat Intelligence Modeling and Identification System Based on Heterogeneous Information Network. IEEE Trans. Knowl. Data Eng. 34(2): 708-722 (2022) - [j425]Shengli Sun, Weiping Li, Yimo Wang, Weilong Liao, Philip S. Yu:
Continuous Monitoring of Maximum Clique Over Dynamic Graphs. IEEE Trans. Knowl. Data Eng. 34(4): 1667-1683 (2022) - [j424]Tao Zhang, Tianqing Zhu, Jing Li, Mengde Han, Wanlei Zhou, Philip S. Yu:
Fairness in Semi-Supervised Learning: Unlabeled Data Help to Reduce Discrimination. IEEE Trans. Knowl. Data Eng. 34(4): 1763-1774 (2022) - [j423]Hao Chen, Chenwei Zhang, Jun Li, Philip S. Yu, Ning Jing:
KGGen: A Generative Approach for Incipient Knowledge Graph Population. IEEE Trans. Knowl. Data Eng. 34(5): 2254-2267 (2022) - [j422]Tianqing Zhu, Dayong Ye, Wei Wang, Wanlei Zhou, Philip S. Yu:
More Than Privacy: Applying Differential Privacy in Key Areas of Artificial Intelligence. IEEE Trans. Knowl. Data Eng. 34(6): 2824-2843 (2022) - [j421]Bao-Yu Liu, Ling Huang, Chang-Dong Wang, Jian-Huang Lai, Philip S. Yu:
Multi-View Consensus Proximity Learning for Clustering. IEEE Trans. Knowl. Data Eng. 34(7): 3405-3417 (2022) - [j420]Senzhang Wang, Jiannong Cao, Philip S. Yu:
Deep Learning for Spatio-Temporal Data Mining: A Survey. IEEE Trans. Knowl. Data Eng. 34(8): 3681-3700 (2022) - [j419]Zhongbao Zhang, Zichang Yin, Jian Wen, Li Sun, Sen Su, Philip S. Yu:
DeepBlue: Bi-Layered LSTM for Tweet popUlarity Estimation. IEEE Trans. Knowl. Data Eng. 34(10): 4737-4752 (2022) - [j418]Fanjin Zhang, Jie Tang, Xueyi Liu, Zhenyu Hou, Yuxiao Dong, Jing Zhang, Xiao Liu, Ruobing Xie, Kai Zhuang, Xu Zhang, Leyu Lin, Philip S. Yu:
Understanding WeChat User Preferences and "Wow" Diffusion. IEEE Trans. Knowl. Data Eng. 34(12): 6033-6046 (2022) - [j417]Shaoxiong Ji, Shirui Pan, Erik Cambria, Pekka Marttinen, Philip S. Yu:
A Survey on Knowledge Graphs: Representation, Acquisition, and Applications. IEEE Trans. Neural Networks Learn. Syst. 33(2): 494-514 (2022) - [j416]Chen Li, Hao Peng, Jianxin Li, Lichao Sun, Lingjuan Lyu, Lihong Wang, Philip S. Yu, Lifang He:
Joint Stance and Rumor Detection in Hierarchical Heterogeneous Graph. IEEE Trans. Neural Networks Learn. Syst. 33(6): 2530-2542 (2022) - [j415]Shenghao Liu, Bang Wang, Laurence T. Yang, Philip S. Yu:
HNF: Hybrid Neural Filtering Based on Centrality-Aware Random Walk for Personalized Recommendation. IEEE Trans. Netw. Sci. Eng. 9(3): 1056-1066 (2022) - [j414]Hao Peng, Ruitong Zhang, Yingtong Dou, Renyu Yang, Jingyi Zhang, Philip S. Yu:
Reinforced Neighborhood Selection Guided Multi-Relational Graph Neural Networks. ACM Trans. Inf. Syst. 40(4): 69:1-69:46 (2022) - [j413]Xiao Pan, Shili Nie, Haibo Hu, Philip S. Yu, Jingfeng Guo:
Reverse Nearest Neighbor Search in Semantic Trajectories for Location-Based Services. IEEE Trans. Serv. Comput. 15(2): 986-999 (2022) - [j412]Wenhua Wang, Yuqun Zhang, Yulei Sui, Yao Wan, Zhou Zhao, Jian Wu, Philip S. Yu, Guandong Xu:
Reinforcement-Learning-Guided Source Code Summarization Using Hierarchical Attention. IEEE Trans. Software Eng. 48(2): 102-119 (2022) - [j411]Zhongyuan Jiang, Xianyu Chen, Jianfeng Ma, Philip S. Yu:
RumorDecay: Rumor Dissemination Interruption for Target Recipients in Social Networks. IEEE Trans. Syst. Man Cybern. Syst. 52(10): 6383-6395 (2022) - [c979]Li Sun, Zhongbao Zhang, Junda Ye, Hao Peng, Jiawei Zhang, Sen Su, Philip S. Yu:
A Self-Supervised Mixed-Curvature Graph Neural Network. AAAI 2022: 4146-4155 - [c978]Qingyun Sun, Jianxin Li, Hao Peng, Jia Wu, Xingcheng Fu, Cheng Ji, Philip S. Yu:
Graph Structure Learning with Variational Information Bottleneck. AAAI 2022: 4165-4174 - [c977]Jianguo Zhang, Kazuma Hashimoto, Yao Wan, Zhiwei Liu, Ye Liu, Caiming Xiong, Philip S. Yu:
Are Pre-trained Transformers Robust in Intent Classification? A Missing Ingredient in Evaluation of Out-of-Scope Intent Detection. ConvAI@ACL 2022: 12-20 - [c976]Byung-Hak Kim, Zhongfen Deng, Philip S. Yu, Varun Ganapathi:
Can Current Explainability Help Provide References in Clinical Notes to Support Humans Annotate Medical Codes? LOUHI@EMNLP 2022: 26-34 - [c975]Zheng Liu, Xiaohan Li, Philip S. Yu:
Mitigating health disparities in EHR via deconfounder. BCB 2022: 6:1-6:6 - [c974]Xing Jia, Yun Xiong, Jiawei Zhang, Yao Zhang, Yangyong Zhu, Philip S. Yu:
Few-Shot Radiology Report Generation via Knowledge Transfer and Multi-modal Alignment. BIBM 2022: 1574-1579 - [c973]Ziwei Fan, Zhiwei Liu, Chen Wang, Peijie Huang, Hao Peng, Philip S. Yu:
Sequential Recommendation with Auxiliary Item Relationships via Multi-Relational Transformer. IEEE Big Data 2022: 525-534 - [c972]Xiaohan Li, Zheng Liu, Luyi Ma, Kaushiki Nag, Stephen D. Guo, Philip S. Yu, Kannan Achan:
Mitigating Frequency Bias in Next-Basket Recommendation via Deconfounders. IEEE Big Data 2022: 616-625 - [c971]Xiaohan Li, Yuqing Liu, Zheng Liu, Philip S. Yu:
Time-aware Hyperbolic Graph Attention Network for Session-based Recommendation. IEEE Big Data 2022: 626-635 - [c970]Shen Wang, Zhengzhang Chen, Jingchao Ni, Haifeng Chen, Philip S. Yu:
Towards Robust Graph Neural Networks via Adversarial Contrastive Learning. IEEE Big Data 2022: 636-645 - [c969]Shen Wang, Liangwei Yang, Jibing Gong, Shaojie Zheng, Shuying Du, Zhiwei Liu, Philip S. Yu:
MetaKRec: Collaborative Meta-Knowledge Enhanced Recommender System. IEEE Big Data 2022: 665-674 - [c968]Yibo Wang, Congying Xia, Guan Wang, Philip S. Yu:
Continuous Prompt Tuning Based Textual Entailment Model for E-commerce Entity Typing. IEEE Big Data 2022: 1383-1388 - [c967]Zhongfen Deng, Wei-Te Chen, Lei Chen, Philip S. Yu:
AE-smnsMLC: Multi-Label Classification with Semantic Matching and Negative Label Sampling for Product Attribute Value Extraction. IEEE Big Data 2022: 1816-1821 - [c966]Jia-Hao Syu, Jerry Chun-Wei Lin, Philip S. Yu:
Double-Environmental Q-Learning for Energy Management System in Smart Grid. IEEE Big Data 2022: 6364-6370 - [c965]Lihua Chen, Ning Yang, Philip S. Yu:
Time Lag Aware Sequential Recommendation. CIKM 2022: 212-221 - [c964]Junhui Li, Wensheng Gan, Yijie Gui, Yongdong Wu, Philip S. Yu:
Frequent Itemset Mining with Local Differential Privacy. CIKM 2022: 1146-1155 - [c963]Jiaqian Ren, Lei Jiang, Hao Peng, Lingjuan Lyu, Zhiwei Liu, Chaochao Chen, Jia Wu, Xu Bai, Philip S. Yu:
Cross-Network Social User Embedding with Hybrid Differential Privacy Guarantees. CIKM 2022: 1685-1695 - [c962]Jiaqian Ren, Lei Jiang, Hao Peng, Yuwei Cao, Jia Wu, Philip S. Yu, Lifang He:
From Known to Unknown: Quality-aware Self-improving Graph Neural Network For Open Set Social Event Detection. CIKM 2022: 1696-1705 - [c961]Li Sun, Junda Ye, Hao Peng, Philip S. Yu:
A Self-supervised Riemannian GNN with Time Varying Curvature for Temporal Graph Learning. CIKM 2022: 1827-1836 - [c960]Qingyun Sun, Jianxin Li, Haonan Yuan, Xingcheng Fu, Hao Peng, Cheng Ji, Qian Li, Philip S. Yu:
Position-aware Structure Learning for Graph Topology-imbalance by Relieving Under-reaching and Over-squashing. CIKM 2022: 1848-1857 - [c959]Yu Wang, Hengrui Zhang, Zhiwei Liu, Liangwei Yang, Philip S. Yu:
ContrastVAE: Contrastive Variational AutoEncoder for Sequential Recommendation. CIKM 2022: 2056-2066 - [c958]Ruitong Zhang, Hao Peng, Yingtong Dou, Jia Wu, Qingyun Sun, Yangyang Li, Jingyi Zhang, Philip S. Yu:
Automating DBSCAN via Deep Reinforcement Learning. CIKM 2022: 2620-2630 - [c957]Philip S. Yu, Olivera Kotevska, Tyler Derr:
PAS: Privacy Algorithms in Systems. CIKM 2022: 5181-5182 - [c956]Xuming Hu, Zhijiang Guo, Yu Fu, Lijie Wen, Philip S. Yu:
Scene Graph Modification as Incremental Structure Expanding. COLING 2022: 5707-5720 - [c955]Yi Xie, Yun Xiong, Yangyong Zhu, Philip S. Yu, Cheng Jin, Qiang Wang, Haihong Li:
Concurrent Transformer for Spatial-Temporal Graph Modeling. DASFAA (3) 2022: 314-321 - [c954]Shicheng Wan, Jieying Deng, Wensheng Gan, Jiahui Chen, Philip S. Yu:
Fast Mining RFM Patterns for Behavioral Analytics. DSAA 2022: 1-10 - [c953]Shu Zhao, Ziwei Du, Jie Chen, Yanping Zhang, Jie Tang, Philip S. Yu:
Hierarchical Representation Learning for Attributed Networks. ICDE 2022: 1497-1498 - [c952]Ya-Wen Teng, Yishuo Shi, De-Nian Yang, Wang-Chien Lee, Philip S. Yu, Ying-Liang Lu, Ming-Syan Chen:
Epidemic Spread Optimization for Disease Containment with NPIs and Vaccination. ICDE 2022: 2845-2858 - [c951]Lu Bai, Yuhang Jiao, Lixin Cui, Luca Rossi, Yue Wang, Philip S. Yu, Edwin R. Hancock:
Learning Graph Convolutional Networks based on Quantum Vertex Information Propagation (Extended Abstract). ICDE 2022: 3132-3133 - [c950]Yao Wan, Yang He, Zhangqian Bi, Jianguo Zhang, Yulei Sui, Hongyu Zhang, Kazuma Hashimoto, Hai Jin, Guandong Xu, Caiming Xiong, Philip S. Yu:
NaturalCC: An Open-Source Toolkit for Code Intelligence. ICSE-Companion 2022: 149-153 - [c949]Jiaqian Ren, Lei Jiang, Hao Peng, Zhiwei Liu, Jia Wu, Philip S. Yu:
Evidential Temporal-aware Graph-based Social Event Detection via Dempster-Shafer Theory. ICWS 2022: 331-336 - [c948]Man-Sheng Chen, Chang-Dong Wang, Dong Huang, Jian-Huang Lai, Philip S. Yu:
Efficient Orthogonal Multi-view Subspace Clustering. KDD 2022: 127-135 - [c947]Zimu Wang, Yue He, Jiashuo Liu, Wenchao Zou, Philip S. Yu, Peng Cui:
Invariant Preference Learning for General Debiasing in Recommendation. KDD 2022: 1969-1978 - [c946]Xixi Wu, Yun Xiong, Yao Zhang, Yizhu Jiao, Caihua Shan, Yiheng Sun, Yangyong Zhu, Philip S. Yu:
CLARE: A Semi-supervised Community Detection Algorithm. KDD 2022: 2059-2069 - [c945]Longbing Cao, Philip S. Yu, Zhilin Zhao:
Shallow and Deep Non-IID Learning on Complex Data. KDD 2022: 4774-4775 - [c944]Pamela Bhattacharya, Jing Gao, Meng Jiang, Mehran Kafai, Srijan Kumar, Qi Li, Neil Shah, Sihong Xie, Philip S. Yu, Ming Zeng:
Joint International Workshop on Misinformation and Misbehavior Mining on the Web & Making a Credible Web for Tomorrow (MIS2-TrueFact). KDD 2022: 4854-4855 - [c943]Chuishi Meng, Yanhua Li, Yu Zheng, Jieping Ye, Qiang Yang, Philip S. Yu, Ouri Wolfson:
The 11th International Workshop on Urban Computing. KDD 2022: 4886-4887 - [c942]Yuwei Cao, William Groves, Tanay Kumar Saha, Joel R. Tetreault, Alejandro Jaimes, Hao Peng, Philip S. Yu:
XLTime: A Cross-Lingual Knowledge Transfer Framework for Temporal Expression Extraction. NAACL-HLT (Findings) 2022: 1931-1942 - [c941]Xuming Hu, Zhijiang Guo, Guanyu Wu, Aiwei Liu, Lijie Wen, Philip S. Yu:
CHEF: A Pilot Chinese Dataset for Evidence-Based Fact-Checking. NAACL-HLT 2022: 3362-3376 - [c940]Shuliang Liu, Xuming Hu, Chenwei Zhang, Shu'ang Li, Lijie Wen, Philip S. Yu:
HiURE: Hierarchical Exemplar Contrastive Learning for Unsupervised Relation Extraction. NAACL-HLT 2022: 5970-5980 - [c939]Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, Lichao Sun, Jundong Li, George H. Chen, Zhihao Jia, Philip S. Yu:
BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs. NeurIPS 2022 - [c938]Yizhen Zheng, Shirui Pan, Vincent C. S. Lee, Yu Zheng, Philip S. Yu:
Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discrimination. NeurIPS 2022 - [c937]Zhiwei Liu, Lin Meng, Fei Jiang, Jiawei Zhang, Philip S. Yu:
Deoscillated Adaptive Graph Collaborative Filtering. TAG-ML 2022: 248-257 - [c936]Zhenyun Hao, Jianing Hao, Zhaohui Peng, Senzhang Wang, Philip S. Yu, Xue Wang, Jian Wang:
Dy-HIEN: Dynamic Evolution based Deep Hierarchical Intention Network for Membership Prediction. WSDM 2022: 363-371 - [c935]Xiaoyun Zhao, Ning Yang, Philip S. Yu:
Multi-Sparse-Domain Collaborative Recommendation via Enhanced Comprehensive Aspect Preference Learning. WSDM 2022: 1452-1460 - [c934]Haoran Yang, Hongxu Chen, Shirui Pan, Lin Li, Philip S. Yu, Guandong Xu:
Dual Space Graph Contrastive Learning. WWW 2022: 1238-1247 - [c933]Ziwei Fan, Zhiwei Liu, Yu Wang, Alice Wang, Zahra Nazari, Lei Zheng, Hao Peng, Philip S. Yu:
Sequential Recommendation via Stochastic Self-Attention. WWW 2022: 2036-2047 - [c932]Liangwei Yang, Zhiwei Liu, Yu Wang, Chen Wang, Ziwei Fan, Philip S. Yu:
Large-scale Personalized Video Game Recommendation via Social-aware Contextualized Graph Neural Network. WWW 2022: 3376-3386 - [i356]Ziwen Du, Ning Yang, Zhonghua Yu, Philip S. Yu:
Learning from Atypical Behavior: Temporary Interest Aware Recommendation Based on Reinforcement Learning. CoRR abs/2201.05970 (2022) - [i355]Xiaoyun Zhao, Ning Yang, Philip S. Yu:
Multi-Sparse-Domain Collaborative Recommendation via Enhanced Comprehensive Aspect Preference Learning. CoRR abs/2201.05973 (2022) - [i354]Ziwei Fan, Zhiwei Liu, Yu Wang, Alice Wang, Zahra Nazari, Lei Zheng, Hao Peng, Philip S. Yu:
Sequential Recommendation via Stochastic Self-Attention. CoRR abs/2201.06035 (2022) - [i353]Haoran Yang, Hongxu Chen, Shirui Pan, Lin Li, Philip S. Yu, Guandong Xu:
Dual Space Graph Contrastive Learning. CoRR abs/2201.07409 (2022) - [i352]Daokun Zhang, Jie Yin, Philip S. Yu:
Link Prediction with Contextualized Self-Supervision. CoRR abs/2201.10069 (2022) - [i351]Liangwei Yang, Zhiwei Liu, Yu Wang, Chen Wang, Ziwei Fan, Philip S. Yu:
Large-scale Personalized Video Game Recommendation via Social-aware Contextualized Graph Neural Network. CoRR abs/2202.03392 (2022) - [i350]Xiaoqin Pan, Xuan Lin, Dongsheng Cao, Xiangxiang Zeng, Philip S. Yu, Lifang He, Ruth Nussinov, Feixiong Cheng:
Deep learning for drug repurposing: methods, databases, and applications. CoRR abs/2202.05145 (2022) - [i349]Xin Zheng, Yixin Liu, Shirui Pan, Miao Zhang, Di Jin, Philip S. Yu:
Graph Neural Networks for Graphs with Heterophily: A Survey. CoRR abs/2202.07082 (2022) - [i348]Wensheng Gan, Guoting Chen, Hongzhi Yin, Philippe Fournier-Viger, Chien-Ming Chen, Philip S. Yu:
Towards Revenue Maximization with Popular and Profitable Products. CoRR abs/2202.13041 (2022) - [i347]Gengsen Huang, Wensheng Gan, Philip S. Yu:
TaSPM: Targeted Sequential Pattern Mining. CoRR abs/2202.13202 (2022) - [i346]Wenting Zhao, Ye Liu, Yao Wan, Philip S. Yu:
Attend, Memorize and Generate: Towards Faithful Table-to-Text Generation in Few Shots. CoRR abs/2203.00732 (2022) - [i345]Zhi-Hong Deng, Chang-Dong Wang, Ling Huang, Jian-Huang Lai, Philip S. Yu:
G3SR: Global Graph Guided Session-based Recommendation. CoRR abs/2203.06467 (2022) - [i344]Xusheng Zhao, Jia Wu, Hao Peng, Amin Beheshti, Jessica Monaghan, David McAlpine, Heivet Hernandez-Perez, Mark Dras, Qiong Dai, Yangyang Li, Philip S. Yu, Lifang He:
Deep Reinforcement Learning Guided Graph Neural Networks for Brain Network Analysis. CoRR abs/2203.10093 (2022) - [i343]Zhiwei Liu, Yongjun Chen, Jia Li, Man Luo, Philip S. Yu, Caiming Xiong:
Improving Contrastive Learning with Model Augmentation. CoRR abs/2203.15508 (2022) - [i342]Tingting Liang, Yixuan Jiang, Congying Xia, Ziqiang Zhao, Yuyu Yin, Philip S. Yu:
Multifaceted Improvements for Conversational Open-Domain Question Answering. CoRR abs/2204.00266 (2022) - [i341]Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, George H. Chen, Zhihao Jia, Philip S. Yu:
PyGOD: A Python Library for Graph Outlier Detection. CoRR abs/2204.12095 (2022) - [i340]Yuwei Cao, William Groves, Tanay Kumar Saha, Joel R. Tetreault, Alex Jaimes, Hao Peng, Philip S. Yu:
XLTime: A Cross-Lingual Knowledge Transfer Framework for Temporal Expression Extraction. CoRR abs/2205.01757 (2022) - [i339]Shuliang Liu, Xuming Hu, Chenwei Zhang, Shu'ang Li, Lijie Wen, Philip S. Yu:
HiURE: Hierarchical Exemplar Contrastive Learning for Unsupervised Relation Extraction. CoRR abs/2205.02225 (2022) - [i338]Jiaqian Ren, Lei Jiang, Hao Peng, Zhiwei Liu, Jia Wu, Philip S. Yu:
Evidential Temporal-aware Graph-based Social Event Detection via Dempster-Shafer Theory. CoRR abs/2205.12179 (2022) - [i337]Shu'ang Li, Xuming Hu, Li Lin, Aiwei Liu, Lijie Wen, Philip S. Yu:
A Multi-level Supervised Contrastive Learning Framework for Low-Resource Natural Language Inference. CoRR abs/2205.15550 (2022) - [i336]Yizhen Zheng, Shirui Pan, Vincent C. S. Lee, Yu Zheng, Philip S. Yu:
Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discrimination. CoRR abs/2206.01535 (2022) - [i335]Wensheng Gan, Gengsen Huang, Jian Weng, Tianlong Gu, Philip S. Yu:
Towards Target Sequential Rules. CoRR abs/2206.04728 (2022) - [i334]Yue Wang, Yao Wan, Lu Bai, Lixin Cui, Zhuo Xu, Ming Li, Philip S. Yu, Edwin R. Hancock:
Collaborative Knowledge Graph Fusion by Exploiting the Open Corpus. CoRR abs/2206.07472 (2022) - [i333]Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, Lichao Sun, Jundong Li, George H. Chen, Zhihao Jia, Philip S. Yu:
Benchmarking Node Outlier Detection on Graphs. CoRR abs/2206.10071 (2022) - [i332]Xuming Hu, Zhijiang Guo, Guanyu Wu, Aiwei Liu, Lijie Wen, Philip S. Yu:
CHEF: A Pilot Chinese Dataset for Evidence-Based Fact-Checking. CoRR abs/2206.11863 (2022) - [i331]Ruitong Zhang, Hao Peng, Yingtong Dou, Jia Wu, Qingyun Sun, Jingyi Zhang, Philip S. Yu:
Automating DBSCAN via Deep Reinforcement Learning. CoRR abs/2208.04537 (2022) - [i330]Lihua Chen, Ning Yang, Philip S. Yu:
Time Lag Aware Sequential Recommendation. CoRR abs/2208.04760 (2022) - [i329]Jiaqian Ren, Lei Jiang, Hao Peng, Yuwei Cao, Jia Wu, Philip S. Yu, Lifang He:
From Known to Unknown: Quality-aware Self-improving Graph Neural Network for Open Set Social Event Detection. CoRR abs/2208.06973 (2022) - [i328]Qingyun Sun, Jianxin Li, Haonan Yuan, Xingcheng Fu, Hao Peng, Cheng Ji, Qian Li, Philip S. Yu:
Position-aware Structure Learning for Graph Topology-imbalance by Relieving Under-reaching and Over-squashing. CoRR abs/2208.08302 (2022) - [i327]Li Sun, Junda Ye, Hao Peng, Philip S. Yu:
A Self-supervised Riemannian GNN with Time Varying Curvature for Temporal Graph Learning. CoRR abs/2208.14073 (2022) - [i326]Jiahui Chen, Xu Guo, Wensheng Gan, Shicheng Wan, Philip S. Yu:
A Generic Algorithm for Top-K On-Shelf Utility Mining. CoRR abs/2208.14230 (2022) - [i325]Yu Wang, Hengrui Zhang, Zhiwei Liu, Liangwei Yang, Philip S. Yu:
ContrastVAE: Contrastive Variational AutoEncoder for Sequential Recommendation. CoRR abs/2209.00456 (2022) - [i324]Jiaqian Ren, Lei Jiang, Hao Peng, Lingjuan Lyu, Zhiwei Liu, Chaochao Chen, Jia Wu, Xu Bai, Philip S. Yu:
Cross-Network Social User Embedding with Hybrid Differential Privacy Guarantees. CoRR abs/2209.01539 (2022) - [i323]Li Sun, Zhongbao Zhang, Jiawei Zhang, Feiyang Wang, Yang Du, Sen Su, Philip S. Yu:
PERFECT: A Hyperbolic Embedding for Joint User and Community Alignment. CoRR abs/2209.02908 (2022) - [i322]Xuming Hu, Zhijiang Guo, Yu Fu, Lijie Wen, Philip S. Yu:
Scene Graph Modification as Incremental Structure Expanding. CoRR abs/2209.09093 (2022) - [i321]Chunkai Zhang, Maohua Lyu, Wensheng Gan, Philip S. Yu:
Totally-ordered Sequential Rules for Utility Maximization. CoRR abs/2209.13501 (2022) - [i320]Yao Chen, Wensheng Gan, Yongdong Wu, Philip S. Yu:
Contrast Pattern Mining: A Survey. CoRR abs/2209.13556 (2022) - [i319]Yazhou Ren, Jingyu Pu, Zhimeng Yang, Jie Xu, Guofeng Li, Xiaorong Pu, Philip S. Yu, Lifang He:
Deep Clustering: A Comprehensive Survey. CoRR abs/2210.04142 (2022) - [i318]Jiayi Sun, Wensheng Gan, Han-Chieh Chao, Philip S. Yu:
Metaverse: Survey, Applications, Security, and Opportunities. CoRR abs/2210.07990 (2022) - [i317]Xixi Wu, Yun Xiong, Yao Zhang, Yizhu Jiao, Caihua Shan, Yiheng Sun, Yangyong Zhu, Philip S. Yu:
CLARE: A Semi-supervised Community Detection Algorithm. CoRR abs/2210.08274 (2022) - [i316]Xuming Hu, Yong Jiang, Aiwei Liu, Zhongqiang Huang, Pengjun Xie, Fei Huang, Lijie Wen, Philip S. Yu:
EnTDA: Entity-to-Text based Data Augmentation Approach for Named Entity Recognition Tasks. CoRR abs/2210.10343 (2022) - [i315]Ziwei Fan, Zhiwei Liu, Chen Wang, Peijie Huang, Hao Peng, Philip S. Yu:
Sequential Recommendation with Auxiliary Item Relationships via Multi-Relational Transformer. CoRR abs/2210.13572 (2022) - [i314]Byung-Hak Kim, Zhongfen Deng, Philip S. Yu, Varun Ganapathi:
Can Current Explainability Help Provide References in Clinical Notes to Support Humans Annotate Medical Codes? CoRR abs/2210.15882 (2022) - [i313]Zheng Liu, Xiaohan Li, Philip S. Yu:
Mitigating Health Disparities in EHR via Deconfounder. CoRR abs/2210.15901 (2022) - [i312]Jiayi Sun, Wensheng Gan, Zefeng Chen, Junhui Li, Philip S. Yu:
Big Data Meets Metaverse: A Survey. CoRR abs/2210.16282 (2022) - [i311]Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu:
Ranking-based Group Identification via Factorized Attention on Social Tripartite Graph. CoRR abs/2211.01830 (2022) - [i310]Yibo Wang, Congying Xia, Guan Wang, Philip S. Yu:
Continuous Prompt Tuning Based Textual Entailment Model for E-commerce Entity Typing. CoRR abs/2211.02483 (2022) - [i309]Xuming Hu, Shiao Meng, Chenwei Zhang, Xiangli Yang, Lijie Wen, Irwin King, Philip S. Yu:
Gradient Imitation Reinforcement Learning for General Low-Resource Information Extraction. CoRR abs/2211.06014 (2022) - [i308]Liangwei Yang, Shen Wang, Jibing Gong, Shaojie Zheng, Shuying Du, Zhiwei Liu, Philip S. Yu:
MetaKRec: Collaborative Meta-Knowledge Enhanced Recommender System. CoRR abs/2211.07104 (2022) - [i307]Xiaohan Li, Zheng Liu, Luyi Ma, Kaushiki Nag, Stephen D. Guo, Philip S. Yu, Kannan Achan:
Mitigating Frequency Bias in Next-Basket Recommendation via Deconfounders. CoRR abs/2211.09072 (2022) - [i306]Liangwei Yang, Shengjie Wang, Yunzhe Tao, Jiankai Sun, Xiaolong Liu, Philip S. Yu, Taiqing Wang:
DGRec: Graph Neural Network for Recommendation with Diversified Embedding Generation. CoRR abs/2211.10486 (2022) - [i305]Jiayi Sun, Wensheng Gan, Han-Chieh Chao, Philip S. Yu, Weiping Ding:
Internet of Behaviors: A Survey. CoRR abs/2211.15588 (2022) - [i304]Li Sun, Junda Ye, Hao Peng, Feiyang Wang, Philip S. Yu:
Self-Supervised Continual Graph Learning in Adaptive Riemannian Spaces. CoRR abs/2211.17068 (2022) - [i303]Jiangshu Du, Wenpeng Yin, Congying Xia, Philip S. Yu:
Learning to Select from Multiple Options. CoRR abs/2212.00301 (2022) - [i302]Hengrui Zhang, Qitian Wu, Yu Wang, Shaofeng Zhang, Junchi Yan, Philip S. Yu:
Localized Contrastive Learning on Graphs. CoRR abs/2212.04604 (2022) - [i301]Gengsen Huang, Wensheng Gan, Philip S. Yu:
Towards Sequence Utility Maximization under Utility Occupancy Measure. CoRR abs/2212.10452 (2022) - [i300]Chunkai Zhang, Yuting Yang, Zilin Du, Wensheng Gan, Philip S. Yu:
HUSP-SP: Faster Utility Mining on Sequence Data. CoRR abs/2212.14255 (2022) - 2021
- [j410]Jerry Chun-Wei Lin, Philippe Fournier-Viger, Vincent S. Tseng, Philip S. Yu:
IEEE Access Special Section Editorial: Utility-Pattern Mining: Theoretical Analytics and Applications. IEEE Access 9: 16604-16607 (2021) - [j409]Xiaobin Rui, Fanrong Meng, Yahui Chai, Zhixiao Wang, Philip S. Yu:
Dismantling Networks by Skeleton Extraction and Greedy Tree Breaking. IEEE Access 9: 84922-84931 (2021) - [j408]Guixiang Ma, Nesreen K. Ahmed, Theodore L. Willke, Philip S. Yu:
Deep graph similarity learning: a survey. Data Min. Knowl. Discov. 35(3): 688-725 (2021) - [j407]Longbing Cao, Qiang Yang, Philip S. Yu:
Data science and AI in FinTech: an overview. Int. J. Data Sci. Anal. 12(2): 81-99 (2021) - [j406]Erik Cambria, Shaoxiong Ji, Shirui Pan, Philip S. Yu:
Knowledge graph representation and reasoning. Neurocomputing 461: 494-496 (2021) - [j405]Chunkai Zhang, Zilin Du, Wensheng Gan, Philip S. Yu:
TKUS: Mining top-k high utility sequential patterns. Inf. Sci. 570: 342-359 (2021) - [j404]Tie Li, Gang Kou, Yi Peng, Philip S. Yu:
A fast diagonal distance metric learning approach for large-scale datasets. Inf. Sci. 571: 225-245 (2021) - [j403]Boyan Wang, Xuegang Hu, Pei-Pei Li, Philip S. Yu:
Cognitive structure learning model for hierarchical multi-label text classification. Knowl. Based Syst. 218: 106876 (2021) - [j402]Zhixiao Wang, Chengcheng Sun, Xiaobin Rui, Philip S. Yu, Lichao Sun:
Localization of multiple diffusion sources based on overlapping community detection. Knowl. Based Syst. 226: 106613 (2021) - [j401]Lixin Cui, Lu Bai, Yue Wang, Philip S. Yu, Edwin R. Hancock:
Fused lasso for feature selection using structural information. Pattern Recognit. 119: 108058 (2021) - [j400]Jianguo Chen, Kenli Li, Keqin Li, Philip S. Yu, Zeng Zeng:
Dynamic Bicycle Dispatching of Dockless Public Bicycle-sharing Systems Using Multi-objective Reinforcement Learning. ACM Trans. Cyber Phys. Syst. 5(4): 34:1-34:24 (2021) - [j399]Xianyu Chen, Zhongyuan Jiang, Hui Li, Jianfeng Ma, Philip S. Yu:
Community Hiding by Link Perturbation in Social Networks. IEEE Trans. Comput. Soc. Syst. 8(3): 704-715 (2021) - [j398]Wensheng Gan, Jerry Chun-Wei Lin, Jiexiong Zhang, Philippe Fournier-Viger, Han-Chieh Chao, Philip S. Yu:
Fast Utility Mining on Sequence Data. IEEE Trans. Cybern. 51(2): 487-500 (2021) - [j397]Bao-Yu Liu, Ling Huang, Chang-Dong Wang, Suohai Fan, Philip S. Yu:
Adaptively Weighted Multiview Proximity Learning for Clustering. IEEE Trans. Cybern. 51(3): 1571-1585 (2021) - [j396]Wensheng Gan, Guoting Chen, Hongzhi Yin, Philippe Fournier-Viger, Chien-Ming Chen, Philip S. Yu:
Towards Revenue Maximization with Popular and Profitable Products. Trans. Data Sci. 2(4): 42:1-42:21 (2021) - [j395]Jie Xu, Zhoujun Li, Feiran Huang, Chaozhuo Li, Philip S. Yu:
Social Image Sentiment Analysis by Exploiting Multimodal Content and Heterogeneous Relations. IEEE Trans. Ind. Informatics 17(4): 2974-2982 (2021) - [j394]Jianguo Chen, Kenli Li, Keqin Li, Philip S. Yu, Zeng Zeng:
Dynamic Planning of Bicycle Stations in Dockless Public Bicycle-sharing System Using Gated Graph Neural Network. ACM Trans. Intell. Syst. Technol. 12(2): 25:1-25:22 (2021) - [j393]Zhenchang Xia, Jia Wu, Libing Wu, Yanjiao Chen, Jian Yang, Philip S. Yu:
A Comprehensive Survey of the Key Technologies and Challenges Surrounding Vehicular Ad Hoc Networks. ACM Trans. Intell. Syst. Technol. 12(4): 37:1-37:30 (2021) - [j392]Yu Huang, Josh Jia-Ching Ying, Philip S. Yu, Vincent S. Tseng:
Dynamic Graph Mining for Multi-weight Multi-destination Route Planning with Deadlines Constraints. ACM Trans. Knowl. Discov. Data 15(1): 3:1-3:32 (2021) - [j391]Wensheng Gan, Jerry Chun-Wei Lin, Jiexiong Zhang, Hongzhi Yin, Philippe Fournier-Viger, Han-Chieh Chao, Philip S. Yu:
Utility Mining Across Multi-Dimensional Sequences. ACM Trans. Knowl. Discov. Data 15(5): 82:1-82:24 (2021) - [j390]Hao Peng, Jianxin Li, Yangqiu Song, Renyu Yang, Rajiv Ranjan, Philip S. Yu, Lifang He:
Streaming Social Event Detection and Evolution Discovery in Heterogeneous Information Networks. ACM Trans. Knowl. Discov. Data 15(5): 89:1-89:33 (2021) - [j389]Wensheng Gan, Jerry Chun-Wei Lin, Philippe Fournier-Viger, Han-Chieh Chao, Vincent S. Tseng, Philip S. Yu:
A Survey of Utility-Oriented Pattern Mining. IEEE Trans. Knowl. Data Eng. 33(4): 1306-1327 (2021) - [j388]Chuan Shi, Xiaotian Han, Li Song, Xiao Wang, Senzhang Wang, Junping Du, Philip S. Yu:
Deep Collaborative Filtering with Multi-Aspect Information in Heterogeneous Networks. IEEE Trans. Knowl. Data Eng. 33(4): 1413-1425 (2021) - [j387]Jianguo Chen, Philip S. Yu:
A Domain Adaptive Density Clustering Algorithm for Data With Varying Density Distribution. IEEE Trans. Knowl. Data Eng. 33(6): 2310-2321 (2021) - [j386]Mingtao Lei, Xi Zhang, Lingyang Chu, Zhefeng Wang, Philip S. Yu, Binxing Fang:
Finding Route Hotspots in Large Labeled Networks. IEEE Trans. Knowl. Data Eng. 33(6): 2479-2492 (2021) - [j385]Hao Peng, Jianxin Li, Senzhang Wang, Lihong Wang, Qiran Gong, Renyu Yang, Bo Li, Philip S. Yu, Lifang He:
Hierarchical Taxonomy-Aware and Attentional Graph Capsule RCNNs for Large-Scale Multi-Label Text Classification. IEEE Trans. Knowl. Data Eng. 33(6): 2505-2519 (2021) - [j384]Linchuan Xu, Jing Wang, Lifang He, Jiannong Cao, Xiaokai Wei, Philip S. Yu, Kenji Yamanishi:
MixSp: A Framework for Embedding Heterogeneous Information Networks With Arbitrary Number of Node and Edge Types. IEEE Trans. Knowl. Data Eng. 33(6): 2627-2639 (2021) - [j383]Zheng Wang, Xiaojun Ye, Chaokun Wang, Jian Cui, Philip S. Yu:
Network Embedding With Completely-Imbalanced Labels. IEEE Trans. Knowl. Data Eng. 33(11): 3634-3647 (2021) - [j382]Lichao Sun, Bokai Cao, Ji Wang, Witawas Srisa-an, Philip S. Yu, Alex D. Leow, Stephen Checkoway:
Kollector: Detecting Fraudulent Activities on Mobile Devices Using Deep Learning. IEEE Trans. Mob. Comput. 20(4): 1465-1476 (2021) - [j381]Youcef Djenouri, Jerry Chun-Wei Lin, Kjetil Nørvåg, Heri Ramampiaro, Philip S. Yu:
Exploring Decomposition for Solving Pattern Mining Problems. ACM Trans. Manag. Inf. Syst. 12(2): 15:1-15:36 (2021) - [j380]Zonghan Wu, Shirui Pan, Fengwen Chen, Guodong Long, Chengqi Zhang, Philip S. Yu:
A Comprehensive Survey on Graph Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 32(1): 4-24 (2021) - [j379]Chang-Dong Wang, Man-Sheng Chen, Ling Huang, Jian-Huang Lai, Philip S. Yu:
Smoothness Regularized Multiview Subspace Clustering With Kernel Learning. IEEE Trans. Neural Networks Learn. Syst. 32(11): 5047-5060 (2021) - [j378]Shaoxu Song, Fei Gao, Aoqian Zhang, Jianmin Wang, Philip S. Yu:
Stream Data Cleaning under Speed and Acceleration Constraints. ACM Trans. Database Syst. 46(3): 10:1-10:44 (2021) - [j377]Wensheng Gan, Jerry Chun-Wei Lin, Philippe Fournier-Viger, Han-Chieh Chao, Philip S. Yu:
Beyond Frequency: Utility Mining with Varied Item-specific Minimum Utility. ACM Trans. Internet Techn. 21(1): 3:1-3:32 (2021) - [j376]He Li, Hang Yuan, Jianbin Huang, Jiangtao Cui, Xiaoke Ma, Senzhang Wang, Jaesoo Yoo, Philip S. Yu:
Group Reassignment for Dynamic Edge Partitioning. IEEE Trans. Parallel Distributed Syst. 32(10): 2477-2490 (2021) - [c931]Li Sun, Zhongbao Zhang, Jiawei Zhang, Feiyang Wang, Hao Peng, Sen Su, Philip S. Yu:
Hyperbolic Variational Graph Neural Network for Modeling Dynamic Graphs. AAAI 2021: 4375-4383 - [c930]Ye Liu, Yao Wan, Lifang He, Hao Peng, Philip S. Yu:
KG-BART: Knowledge Graph-Augmented BART for Generative Commonsense Reasoning. AAAI 2021: 6418-6425 - [c929]Xiaohan Li, Zhiwei Liu, Stephen D. Guo, Zheng Liu, Hao Peng, Philip S. Yu, Kannan Achan:
Pre-training Recommender Systems via Reinforced Attentive Multi-relational Graph Neural Network. IEEE BigData 2021: 457-468 - [c928]Fuxin Ren, Zhongbao Zhang, Yang Yan, Zhi Wang, Sen Su, Philip S. Yu:
HAMLET: Hierarchical Attention-based Model with muLti-task sElf-Training for user profiling. IEEE BigData 2021: 500-509 - [c927]Shen Wang, Xiaokai Wei, Cícero Nogueira dos Santos, Zhiguo Wang, Ramesh Nallapati, Andrew O. Arnold, Philip S. Yu:
Knowledge Graph Representation via Hierarchical Hyperbolic Neural Graph Embedding. IEEE BigData 2021: 540-549 - [c926]Shaika Chowdhury, Halid Ziya Yerebakan, Yoshihisa Shinagawa, Philip S. Yu:
MedTextSeg: A Deep Dual Sequential Model for Section Segmentation in Medical Reports. IEEE BigData 2021: 1582-1588 - [c925]Chen Wang, Yingtong Dou, Min Chen, Jia Chen, Zhiwei Liu, Philip S. Yu:
Deep Fraud Detection on Non-attributed Graph. IEEE BigData 2021: 5470-5473 - [c924]Nooshin Mojab, Vahid Noroozi, Abdullah Aleem, Manoj Prabhakar Nallabothula, Joseph Baker, Dimitri T. Azar, Mark Rosenblatt, R. V. Paul Chan, Darvin Yi, Philip S. Yu, Joelle A. Hallak:
I-ODA, Real-world Multi-modal Longitudinal Data for Ophthalmic Applications. HEALTHINF 2021: 566-574 - [c923]Nooshin Mojab, Philip S. Yu, Joelle A. Hallak, Darvin Yi:
CvS: Classification via Segmentation For Small Datasets. BMVC 2021: 174 - [c922]Ziwei Fan, Zhiwei Liu, Jiawei Zhang, Yun Xiong, Lei Zheng, Philip S. Yu:
Continuous-Time Sequential Recommendation with Temporal Graph Collaborative Transformer. CIKM 2021: 433-442 - [c921]Li He, Hongxu Chen, Dingxian Wang, Shoaib Jameel, Philip S. Yu, Guandong Xu:
Click-Through Rate Prediction with Multi-Modal Hypergraphs. CIKM 2021: 690-699 - [c920]Yicong Li, Hongxu Chen, Xiangguo Sun, Zhenchao Sun, Lin Li, Lizhen Cui, Philip S. Yu, Guandong Xu:
Hyperbolic Hypergraphs for Sequential Recommendation. CIKM 2021: 988-997 - [c919]Xiaosu Wang, Yun Xiong, Hao Niu, Jingwen Yue, Yangyong Zhu, Philip S. Yu:
Improving Chinese Character Representation with Formation Graph Attention Network. CIKM 2021: 1999-2009 - [c918]Ziwei Fan, Zhiwei Liu, Shen Wang, Lei Zheng, Philip S. Yu:
Modeling Sequences as Distributions with Uncertainty for Sequential Recommendation. CIKM 2021: 3019-3023 - [c917]Chaozhuo Li, Senzhang Wang, Feiran Huang, Jie Xu, Philip S. Yu:
Hubness-aware User Identity Linkage. CIKM 2021: 3196-3200 - [c916]Chen Li, Xutan Peng, Hao Peng, Jia Wu, Lihong Wang, Philip S. Yu, Jianxin Li, Lichao Sun:
Graph-based Semi-Supervised Learning by Strengthening Local Label Consistency. CIKM 2021: 3201-3205 - [c915]Yu Wang, Zhiwei Liu, Ziwei Fan, Lichao Sun, Philip S. Yu:
DSKReG: Differentiable Sampling on Knowledge Graph for Recommendation with Relational GNN. CIKM 2021: 3513-3517 - [c914]Chen Wang, Yueqing Liang, Zhiwei Liu, Tao Zhang, Philip S. Yu:
Pre-training Graph Neural Network for Cross Domain Recommendation. CogMI 2021: 140-145 - [c913]Xinyu Wen, Zhaohui Peng, Shanshan Huang, Senzhang Wang, Philip S. Yu:
MISS: A Multi-user Identification Network for Shared-Account Session-Aware Recommendation. DASFAA (3) 2021: 228-243 - [c912]Xiaokang Xu, Zhaohui Peng, Senzhang Wang, Shanshan Huang, Philip S. Yu, Zhenyun Hao, Jian Wang, Xue Wang:
AE-UPCP: Seeking Potential Membership Users by Audience Expansion Combining User Preference with Consumption Pattern. DASFAA (2) 2021: 392-399 - [c911]Ye Liu, Yao Wan, Jian-Guo Zhang, Wenting Zhao, Philip S. Yu:
Enriching Non-Autoregressive Transformer with Syntactic and Semantic Structures for Neural Machine Translation. EACL 2021: 1235-1244 - [c910]Ye Liu, Jian-Guo Zhang, Yao Wan, Congying Xia, Lifang He, Philip S. Yu:
HETFORMER: Heterogeneous Transformer with Sparse Attention for Long-Text Extractive Summarization. EMNLP (1) 2021: 146-154 - [c909]Ye Liu, Kazuma Hashimoto, Yingbo Zhou, Semih Yavuz, Caiming Xiong, Philip S. Yu:
Dense Hierarchical Retrieval for Open-domain Question Answering. EMNLP (Findings) 2021: 188-200 - [c908]Xuming Hu, Chenwei Zhang, Fukun Ma, Chenyao Liu, Lijie Wen, Philip S. Yu:
Semi-supervised Relation Extraction via Incremental Meta Self-Training. EMNLP (Findings) 2021: 487-496 - [c907]Jian-Guo Zhang, Trung Bui, Seunghyun Yoon, Xiang Chen, Zhiwei Liu, Congying Xia, Quan Hung Tran, Walter Chang, Philip S. Yu:
Few-Shot Intent Detection via Contrastive Pre-Training and Fine-Tuning. EMNLP (1) 2021: 1906-1912 - [c906]Xuming Hu, Chenwei Zhang, Yawen Yang, Xiaohe Li, Li Lin, Lijie Wen, Philip S. Yu:
Gradient Imitation Reinforcement Learning for Low Resource Relation Extraction. EMNLP (1) 2021: 2737-2746 - [c905]Wenting Zhao, Ye Liu, Yao Wan, Philip S. Yu:
Attend, Memorize and Generate: Towards Faithful Table-to-Text Generation in Few Shots. EMNLP (Findings) 2021: 4106-4117 - [c904]Tao Zhang, Congying Xia, Philip S. Yu, Zhiwei Liu, Shu Zhao:
PDALN: Progressive Domain Adaptation over a Pre-trained Model for Low-Resource Cross-Domain Named Entity Recognition. EMNLP (1) 2021: 5441-5451 - [c903]Hsi-Wen Chen, Hong-Han Shuai, De-Nian Yang, Wang-Chien Lee, Chuan Shi, Philip S. Yu, Ming-Syan Chen:
Structure-Aware Parameter-Free Group Query via Heterogeneous Information Network Transformer. ICDE 2021: 2075-2080 - [c902]Xingcheng Fu, Jianxin Li, Jia Wu, Qingyun Sun, Cheng Ji, Senzhang Wang, Jiajun Tan, Hao Peng, Philip S. Yu:
ACE-HGNN: Adaptive Curvature Exploration Hyperbolic Graph Neural Network. ICDM 2021: 111-120 - [c901]Mehrnaz Najafi, Lifang He, Philip S. Yu:
Outlier-Robust Multi-View Subspace Clustering with Prior Constraints. ICDM 2021: 439-448 - [c900]Haoran Yang, Hongxu Chen, Lin Li, Philip S. Yu, Guandong Xu:
Hyper Meta-Path Contrastive Learning for Multi-Behavior Recommendation. ICDM 2021: 787-796 - [c899]Wenwei Ke, Chuanren Liu, Xiangfu Shi, Yiqiao Dai, Philip S. Yu, Xiaoqiang Zhu:
Addressing Exposure Bias in Uplift Modeling for Large-scale Online Advertising. ICDM 2021: 1156-1161 - [c898]Xiaosu Wang, Yun Xiong, Hao Niu, Jingwen Yue, Yangyong Zhu, Philip S. Yu:
BioHanBERT: A Hanzi-aware Pre-trained Language Model for Chinese Biomedical Text Mining. ICDM 2021: 1415-1420 - [c897]Yongshan Zhang, Xinxin Wang, Zhihua Cai, Yicong Zhou, Philip S. Yu:
Tensor-Based Unsupervised Multi-View Feature Selection for Image Recognition. ICME 2021: 1-6 - [c896]Gongxu Luo, Jianxin Li, Hao Peng, Carl Yang, Lichao Sun, Philip S. Yu, Lifang He:
Graph Entropy Guided Node Embedding Dimension Selection for Graph Neural Networks. IJCAI 2021: 2767-2774 - [c895]Shoujin Wang, Liang Hu, Yan Wang, Xiangnan He, Quan Z. Sheng, Mehmet A. Orgun, Longbing Cao, Francesco Ricci, Philip S. Yu:
Graph Learning based Recommender Systems: A Review. IJCAI 2021: 4644-4652 - [c894]Jiangshu Du, Yingtong Dou, Congying Xia, Limeng Cui, Jing Ma, Philip S. Yu:
Cross-lingual COVID-19 Fake News Detection. ICDM (Workshops) 2021: 859-862 - [c893]Yue He, Yancheng Dong, Peng Cui, Yuhang Jiao, Xiaowei Wang, Ji Liu, Philip S. Yu:
Purify and Generate: Learning Faithful Item-to-Item Graph from Noisy User-Item Interaction Behaviors. KDD 2021: 3002-3010 - [c892]Wei Jin, Yao Ma, Yiqi Wang, Xiaorui Liu, Jiliang Tang, Yukuo Cen, Jiezhong Qiu, Jie Tang, Chuan Shi, Yanfang Ye, Jiawei Zhang, Philip S. Yu:
Graph Representation Learning: Foundations, Methods, Applications and Systems. KDD 2021: 4044-4045 - [c891]Subhabrata Mukherjee, Qi Li, Sihong Xie, Philip S. Yu, Jing Gao:
The Third International TrueFact Workshop: Making a Credible Web for Tomorrow. KDD 2021: 4143-4144 - [c890]Jianpeng Xu, Lingfei Wu, Xiaolin Pang, Mohit Sharma, Dawei Yin, George Karypis, Justin Basilico, Philip S. Yu:
2nd International Workshop on Industrial Recommendation Systems (IRS). KDD 2021: 4173-4174 - [c889]Congying Xia, Wenpeng Yin, Yihao Feng, Philip S. Yu:
Incremental Few-shot Text Classification with Multi-round New Classes: Formulation, Dataset and System. NAACL-HLT 2021: 1351-1360 - [c888]Zhongfen Deng, Hao Peng, Dongxiao He, Jianxin Li, Philip S. Yu:
HTCInfoMax: A Global Model for Hierarchical Text Classification via Information Maximization. NAACL-HLT 2021: 3259-3265 - [c887]Hengrui Zhang, Qitian Wu, Junchi Yan, David Wipf, Philip S. Yu:
From Canonical Correlation Analysis to Self-supervised Graph Neural Networks. NeurIPS 2021: 76-89 - [c886]Charu C. Aggarwal, Yao Li, Philip S. Yu:
Signature-Based Anomaly Detection in Networks. SDM 2021: 109-117 - [c885]Senzhang Wang, Meiyue Zhang, Hao Miao, Philip S. Yu:
MT-STNets: Multi-Task Spatial-Temporal Networks for Multi-Scale Traffic Prediction. SDM 2021: 504-512 - [c884]Zhiwei Liu, Ziwei Fan, Yu Wang, Philip S. Yu:
Augmenting Sequential Recommendation with Pseudo-Prior Items via Reversely Pre-training Transformer. SIGIR 2021: 1608-1612 - [c883]Zheng Liu, Xiaohan Li, Zeyu You, Tao Yang, Wei Fan, Philip S. Yu:
Medical Triage Chatbot Diagnosis Improvement via Multi-relational Hyperbolic Graph Neural Network. SIGIR 2021: 1965-1969 - [c882]Congying Xia, Caiming Xiong, Philip S. Yu:
Pseudo Siamese Network for Few-shot Intent Generation. SIGIR 2021: 2005-2009 - [c881]Yingtong Dou, Kai Shu, Congying Xia, Philip S. Yu, Lichao Sun:
User Preference-aware Fake News Detection. SIGIR 2021: 2051-2055 - [c880]Liangwei Yang, Zhiwei Liu, Yingtong Dou, Jing Ma, Philip S. Yu:
ConsisRec: Enhancing GNN for Social Recommendation via Consistent Neighbor Aggregation. SIGIR 2021: 2141-2145 - [c879]Huidi Chen, Yun Xiong, Yangyong Zhu, Philip S. Yu:
Highly Liquid Temporal Interaction Graph Embeddings. WWW 2021: 1639-1648 - [c878]Shen Wang, Xiaokai Wei, Cícero Nogueira dos Santos, Zhiguo Wang, Ramesh Nallapati, Andrew O. Arnold, Bing Xiang, Philip S. Yu, Isabel F. Cruz:
Mixed-Curvature Multi-Relational Graph Neural Network for Knowledge Graph Completion. WWW 2021: 1761-1771 - [c877]Qingyun Sun, Jianxin Li, Hao Peng, Jia Wu, Yuanxing Ning, Philip S. Yu, Lifang He:
SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism. WWW 2021: 2081-2091 - [c876]Yuwei Cao, Hao Peng, Jia Wu, Yingtong Dou, Jianxin Li, Philip S. Yu:
Knowledge-Preserving Incremental Social Event Detection via Heterogeneous GNNs. WWW 2021: 3383-3395 - [i299]Di Jin, Zhizhi Yu, Pengfei Jiao, Shirui Pan, Philip S. Yu, Weixiong Zhang:
A Survey of Community Detection Approaches: From Statistical Modeling to Deep Learning. CoRR abs/2101.01669 (2021) - [i298]Xiaohan Li, Mengqi Zhang, Shu Wu, Zheng Liu, Liang Wang, Philip S. Yu:
Dynamic Graph Collaborative Filtering. CoRR abs/2101.02844 (2021) - [i297]Zheng Liu, Xiaohan Li, Hao Peng, Lifang He, Philip S. Yu:
Heterogeneous Similarity Graph Neural Network on Electronic Health Records. CoRR abs/2101.06800 (2021) - [i296]Jianguo Chen, Kenli Li, Keqin Li, Philip S. Yu, Zeng Zeng:
Dynamic Planning of Bicycle Stations in Dockless Public Bicycle-sharing System Using Gated Graph Neural Network. CoRR abs/2101.07425 (2021) - [i295]Jianguo Chen, Kenli Li, Keqin Li, Philip S. Yu, Zeng Zeng:
Dynamic Bicycle Dispatching of Dockless Public Bicycle-sharing Systems using Multi-objective Reinforcement Learning. CoRR abs/2101.07437 (2021) - [i294]Qingyun Sun, Hao Peng, Jianxin Li, Jia Wu, Yuanxing Ning, Philip S. Yu, Lifang He:
SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism. CoRR abs/2101.08170 (2021) - [i293]Yuwei Cao, Hao Peng, Jia Wu, Yingtong Dou, Jianxin Li, Philip S. Yu:
Knowledge-Preserving Incremental Social Event Detection via Heterogeneous GNNs. CoRR abs/2101.08747 (2021) - [i292]Ye Liu, Yao Wan, Jian-Guo Zhang, Wenting Zhao, Philip S. Yu:
Enriching Non-Autoregressive Transformer with Syntactic and SemanticStructures for Neural Machine Translation. CoRR abs/2101.08942 (2021) - [i291]Yixin Liu, Shirui Pan, Ming Jin, Chuan Zhou, Feng Xia, Philip S. Yu:
Graph Self-Supervised Learning: A Survey. CoRR abs/2103.00111 (2021) - [i290]Fanjin Zhang, Jie Tang, Xueyi Liu, Zhenyu Hou, Yuxiao Dong, Jing Zhang, Xiao Liu, Ruobing Xie, Kai Zhuang, Xu Zhang, Leyu Lin, Philip S. Yu:
Understanding WeChat User Preferences and "Wow" Diffusion. CoRR abs/2103.02930 (2021) - [i289]Zi-Yuan Hu, Jin Huang, Zhi-Hong Deng, Chang-Dong Wang, Ling Huang, Jian-Huang Lai, Philip S. Yu:
BCFNet: A Balanced Collaborative Filtering Network with Attention Mechanism. CoRR abs/2103.06105 (2021) - [i288]Yunbo Wang, Haixu Wu, Jianjin Zhang, Zhifeng Gao, Jianmin Wang, Philip S. Yu, Mingsheng Long:
PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning. CoRR abs/2103.09504 (2021) - [i287]Mehrnaz Najafi, Philip S. Yu:
An Introduction to Robust Graph Convolutional Networks. CoRR abs/2103.14807 (2021) - [i286]Chunkai Zhang, Zilin Du, Quanjian Dai, Wensheng Gan, Jian Weng, Philip S. Yu:
TUSQ: Targeted High-Utility Sequence Querying. CoRR abs/2103.16615 (2021) - [i285]Hao Peng, Jianxin Li, Yangqiu Song, Renyu Yang, Rajiv Ranjan, Philip S. Yu, Lifang He:
Streaming Social Event Detection and Evolution Discovery in Heterogeneous Information Networks. CoRR abs/2104.00853 (2021) - [i284]Li Sun, Zhongbao Zhang, Jiawei Zhang, Feiyang Wang, Hao Peng, Sen Su, Philip S. Yu:
Hyperbolic Variational Graph Neural Network for Modeling Dynamic Graphs. CoRR abs/2104.02228 (2021) - [i283]Nooshin Mojab, Vahid Noroozi, Abdullah Aleem, Manoj Prabhakar Nallabothula, Joseph Baker, Dimitri T. Azar, Mark Rosenblatt, R. V. Paul Chan, Darvin Yi, Philip S. Yu, Joelle A. Hallak:
I-ODA, Real-World Multi-modal Longitudinal Data for OphthalmicApplications. CoRR abs/2104.02609 (2021) - [i282]Zhongfen Deng, Hao Peng, Dongxiao He, Jianxin Li, Philip S. Yu:
HTCInfoMax: A Global Model for Hierarchical Text Classification via Information Maximization. CoRR abs/2104.05220 (2021) - [i281]Hao Peng, Ruitong Zhang, Yingtong Dou, Renyu Yang, Jingyi Zhang, Philip S. Yu:
Reinforced Neighborhood Selection Guided Multi-Relational Graph Neural Networks. CoRR abs/2104.07886 (2021) - [i280]Jianxin Li, Hao Peng, Yuwei Cao, Yingtong Dou, Hekai Zhang, Philip S. Yu, Lifang He:
Higher-Order Attribute-Enhancing Heterogeneous Graph Neural Networks. CoRR abs/2104.07892 (2021) - [i279]Congying Xia, Wenpeng Yin, Yihao Feng, Philip S. Yu:
Incremental Few-shot Text Classification with Multi-round New Classes: Formulation, Dataset and System. CoRR abs/2104.11882 (2021) - [i278]Yingtong Dou, Kai Shu, Congying Xia, Philip S. Yu, Lichao Sun:
User Preference-aware Fake News Detection. CoRR abs/2104.12259 (2021) - [i277]Zhiwei Liu, Ziwei Fan, Yu Wang, Philip S. Yu:
Augmenting Sequential Recommendation with Pseudo-Prior Items via Reversely Pre-training Transformer. CoRR abs/2105.00522 (2021) - [i276]Congying Xia, Caiming Xiong, Philip S. Yu:
Pseudo Siamese Network for Few-shot Intent Generation. CoRR abs/2105.00896 (2021) - [i275]Liangwei Yang, Zhiwei Liu, Yingtong Dou, Jing Ma, Philip S. Yu:
ConsisRec: Enhancing GNN for Social Recommendation via Consistent Neighbor Aggregation. CoRR abs/2105.02254 (2021) - [i274]Mehrnaz Najafi, Lifang He, Philip S. Yu:
Error-Robust Multi-View Clustering: Progress, Challenges and Opportunities. CoRR abs/2105.03058 (2021) - [i273]Gongxu Luo, Jianxin Li, Hao Peng, Carl Yang, Lichao Sun, Philip S. Yu, Lifang He:
Graph Entropy Guided Node Embedding Dimension Selection for Graph Neural Networks. CoRR abs/2105.03178 (2021) - [i272]Shoujin Wang, Liang Hu, Yan Wang, Xiangnan He, Quan Z. Sheng, Mehmet A. Orgun, Longbing Cao, Francesco Ricci, Philip S. Yu:
Graph Learning based Recommender Systems: A Review. CoRR abs/2105.06339 (2021) - [i271]Jianxin Li, Xingcheng Fu, Hao Peng, Senzhang Wang, Shijie Zhu, Qingyun Sun, Philip S. Yu, Lifang He:
A Robust and Generalized Framework for Adversarial Graph Embedding. CoRR abs/2105.10651 (2021) - [i270]Xing Su, Shan Xue, Fanzhen Liu, Jia Wu, Jian Yang, Chuan Zhou, Wenbin Hu, Cécile Paris, Surya Nepal, Di Jin, Quan Z. Sheng, Philip S. Yu:
A Comprehensive Survey on Community Detection with Deep Learning. CoRR abs/2105.12584 (2021) - [i269]Qianren Mao, Xi Li, Hao Peng, Bang Liu, Shu Guo, Jianxin Li, Lihong Wang, Philip S. Yu:
Attend and Select: A Segment Attention based Selection Mechanism for Microblog Hashtag Generation. CoRR abs/2106.03151 (2021) - [i268]Siddharth Bhatia, Mohit Wadhwa, Philip S. Yu, Bryan Hooi:
Sketch-Based Streaming Anomaly Detection in Dynamic Graphs. CoRR abs/2106.04486 (2021) - [i267]Jianguo Zhang, Kazuma Hashimoto, Yao Wan, Ye Liu, Caiming Xiong, Philip S. Yu:
Are Pretrained Transformers Robust in Intent Classification? A Missing Ingredient in Evaluation of Out-of-Scope Intent Detection. CoRR abs/2106.04564 (2021) - [i266]Ziwei Fan, Zhiwei Liu, Lei Zheng, Shen Wang, Philip S. Yu:
Modeling Sequences as Distributions with Uncertainty for Sequential Recommendation. CoRR abs/2106.06165 (2021) - [i265]Qian Li, Hao Peng, Jianxin Li, Yuanxing Ning, Lihong Wang, Philip S. Yu, Zheng Wang:
Reinforcement Learning-based Dialogue Guided Event Extraction to Exploit Argument Relations. CoRR abs/2106.12384 (2021) - [i264]Hengrui Zhang, Qitian Wu, Junchi Yan, David Wipf, Philip S. Yu:
From Canonical Correlation Analysis to Self-supervised Graph Neural Networks. CoRR abs/2106.12484 (2021) - [i263]Qiaomin Yi, Ning Yang, Philip S. Yu:
Dual Adversarial Variational Embedding for Robust Recommendation. CoRR abs/2106.15779 (2021) - [i262]Qian Li, Hao Peng, Jianxin Li, Yiming Hei, Rui Sun, Jiawei Sheng, Shu Guo, Lihong Wang, Philip S. Yu:
Deep Learning Schema-based Event Extraction: Literature Review and Current Trends. CoRR abs/2107.02126 (2021) - [i261]Zhiwei Liu, Yongjun Chen, Jia Li, Philip S. Yu, Julian J. McAuley, Caiming Xiong:
Contrastive Self-supervised Sequential Recommendation with Robust Augmentation. CoRR abs/2108.06479 (2021) - [i260]Ziwei Fan, Zhiwei Liu, Jiawei Zhang, Yun Xiong, Lei Zheng, Philip S. Yu:
Continuous-Time Sequential Recommendation with Temporal Graph Collaborative Transformer. CoRR abs/2108.06625 (2021) - [i259]Yicong Li, Hongxu Chen, Xiangguo Sun, Zhenchao Sun, Lin Li, Lizhen Cui, Philip S. Yu, Guandong Xu:
Hyperbolic Hypergraphs for Sequential Recommendation. CoRR abs/2108.08134 (2021) - [i258]Yu Wang, Zhiwei Liu, Ziwei Fan, Lichao Sun, Philip S. Yu:
DSKReG: Differentiable Sampling on Knowledge Graph for Recommendation with Relational GNN. CoRR abs/2108.11883 (2021) - [i257]Li He, Hongxu Chen, Dingxian Wang, Shoaib Jameel, Philip S. Yu, Guandong Xu:
Click-Through Rate Prediction with Multi-Modal Hypergraphs. CoRR abs/2109.02398 (2021) - [i256]Haoran Yang, Hongxu Chen, Lin Li, Philip S. Yu, Guandong Xu:
Hyper Meta-Path Contrastive Learning for Multi-Behavior Recommendation. CoRR abs/2109.02859 (2021) - [i255]Jian-Guo Zhang, Trung Bui, Seunghyun Yoon, Xiang Chen, Zhiwei Liu, Congying Xia, Quan Hung Tran, Walter Chang, Philip S. Yu:
Few-Shot Intent Detection via Contrastive Pre-Training and Fine-Tuning. CoRR abs/2109.06349 (2021) - [i254]Xuming Hu, Chenwei Zhang, Yawen Yang, Xiaohe Li, Li Lin, Lijie Wen, Philip S. Yu:
Gradient Imitation Reinforcement Learning for Low Resource Relation Extraction. CoRR abs/2109.06415 (2021) - [i253]Chen Wang, Yingtong Dou, Min Chen, Jia Chen, Zhiwei Liu, Philip S. Yu:
Deep Fraud Detection on Non-attributed Graph. CoRR abs/2110.01171 (2021) - [i252]Ye Liu, Jian-Guo Zhang, Yao Wan, Congying Xia, Lifang He, Philip S. Yu:
HETFORMER: Heterogeneous Transformer with Sparse Attention for Long-Text Extractive Summarization. CoRR abs/2110.06388 (2021) - [i251]Jiangshu Du, Yingtong Dou, Congying Xia, Limeng Cui, Jing Ma, Philip S. Yu:
Cross-lingual COVID-19 Fake News Detection. CoRR abs/2110.06495 (2021) - [i250]Xingcheng Fu, Jianxin Li, Jia Wu, Qingyun Sun, Cheng Ji, Senzhang Wang, Jiajun Tan, Hao Peng, Philip S. Yu:
ACE-HGNN: Adaptive Curvature Exploration Hyperbolic Graph Neural Network. CoRR abs/2110.07888 (2021) - [i249]Ye Liu, Kazuma Hashimoto, Yingbo Zhou, Semih Yavuz, Caiming Xiong, Philip S. Yu:
Dense Hierarchical Retrieval for Open-Domain Question Answering. CoRR abs/2110.15439 (2021) - [i248]Nooshin Mojab, Philip S. Yu, Joelle A. Hallak, Darvin Yi:
CvS: Classification via Segmentation For Small Datasets. CoRR abs/2111.00042 (2021) - [i247]Chunkai Zhang, Quanjian Dai, Zilin Du, Wensheng Gan, Jian Weng, Philip S. Yu:
Utility-driven Mining of Contiguous Sequences. CoRR abs/2111.00247 (2021) - [i246]Chen Wang, Yueqing Liang, Zhiwei Liu, Tao Zhang, Philip S. Yu:
Pre-training Graph Neural Network for Cross Domain Recommendation. CoRR abs/2111.08268 (2021) - [i245]Zhiwei Liu, Liangwei Yang, Ziwei Fan, Hao Peng, Philip S. Yu:
Federated Social Recommendation with Graph Neural Network. CoRR abs/2111.10778 (2021) - [i244]Yicong Li, Hongxu Chen, Yile Li, Lin Li, Philip S. Yu, Guandong Xu:
Reinforcement Learning based Path Exploration for Sequential Explainable Recommendation. CoRR abs/2111.12262 (2021) - [i243]Chuanpan Zheng, Xiaoliang Fan, Shirui Pan, Zonghan Wu, Cheng Wang, Philip S. Yu:
Spatio-Temporal Joint Graph Convolutional Networks for Traffic Forecasting. CoRR abs/2111.13684 (2021) - [i242]Xiaohan Li, Zhiwei Liu, Stephen D. Guo, Zheng Liu, Hao Peng, Philip S. Yu, Kannan Achan:
Pre-training Recommender Systems via Reinforced Attentive Multi-relational Graph Neural Network. CoRR abs/2111.14036 (2021) - [i241]Gengsen Huang, Wensheng Gan, Jian Weng, Philip S. Yu:
US-Rule: Discovering Utility-driven Sequential Rules. CoRR abs/2111.15020 (2021) - [i240]Li Sun, Zhongbao Zhang, Junda Ye, Hao Peng, Jiawei Zhang, Sen Su, Philip S. Yu:
A Self-supervised Mixed-curvature Graph Neural Network. CoRR abs/2112.05393 (2021) - [i239]Yiqi Wang, Chaozhuo Li, Zheng Liu, Mingzheng Li, Jiliang Tang, Xing Xie, Lei Chen, Philip S. Yu:
An Adaptive Graph Pre-training Framework for Localized Collaborative Filtering. CoRR abs/2112.07191 (2021) - [i238]Chaozhuo Li, Senzhang Wang, Zheng Liu, Xing Xie, Lei Chen, Philip S. Yu:
Semi-Supervised Variational User Identity Linkage via Noise-Aware Self-Learning. CoRR abs/2112.07373 (2021) - [i237]Qingyun Sun, Jianxin Li, Hao Peng, Jia Wu, Xingcheng Fu, Cheng Ji, Philip S. Yu:
Graph Structure Learning with Variational Information Bottleneck. CoRR abs/2112.08903 (2021) - [i236]He Huang, Wei Tang, Jiawei Zhang, Philip S. Yu:
Translational Concept Embedding for Generalized Compositional Zero-shot Learning. CoRR abs/2112.10871 (2021) - 2020
- [j375]Yuqing Zhu, Philip S. Yu, Guolei Yi, Mengying Guo, Wenlong Ma, Jianxun Liu, Yungang Bao:
Logless one-phase commit made possible for highly-available datastores. Distributed Parallel Databases 38(1): 101-126 (2020) - [j374]Tianqing Zhu, Ping Xiong, Gang Li, Wanlei Zhou, Philip S. Yu:
Differentially private model publishing in cyber physical systems. Future Gener. Comput. Syst. 108: 1297-1306 (2020) - [j373]Linchuan Xu, Xiaokai Wei, Jiannong Cao, Philip S. Yu:
ICANE: interaction content-aware network embedding via co-embedding of nodes and edges. Int. J. Data Sci. Anal. 9(4): 401-414 (2020) - [j372]Wensheng Gan, Jerry Chun-Wei Lin, Jiexiong Zhang, Han-Chieh Chao, Hamido Fujita, Philip S. Yu:
ProUM: Projection-based utility mining on sequence data. Inf. Sci. 513: 222-240 (2020) - [j371]Hao Peng, Hongfei Wang, Bowen Du, Md. Zakirul Alam Bhuiyan, Hongyuan Ma, Jianwei Liu, Lihong Wang, Zeyu Yang, Linfeng Du, Senzhang Wang, Philip S. Yu:
Spatial temporal incidence dynamic graph neural networks for traffic flow forecasting. Inf. Sci. 521: 277-290 (2020) - [j370]Jianping Cao, Senzhang Wang, Danyan Wen, Zhaohui Peng, Philip S. Yu, Fei-Yue Wang:
Mutual clustering on comparative texts via heterogeneous information networks. Knowl. Inf. Syst. 62(1): 175-202 (2020) - [j369]Xinghua Wang, Zhaohui Peng, Senzhang Wang, Philip S. Yu, Wenjing Fu, Xiaokang Xu, Xiaoguang Hong:
CDLFM: cross-domain recommendation for cold-start users via latent feature mapping. Knowl. Inf. Syst. 62(5): 1723-1750 (2020) - [j368]Tingting Liang, Lifang He, Chun-Ta Lu, Liang Chen, Haochao Ying, Philip S. Yu, Jian Wu:
CAMAR: a broad learning based context-aware recommender for mobile applications. Knowl. Inf. Syst. 62(8): 3291-3319 (2020) - [j367]Tingting Liang, Lei Zheng, Liang Chen, Yao Wan, Philip S. Yu, Jian Wu:
Multi-view factorization machines for mobile app recommendation based on hierarchical attention. Knowl. Based Syst. 187 (2020) - [j366]Yuhui Zhao, Ning Yang, Tao Lin, Philip S. Yu:
Deep Collaborative Embedding for information cascade prediction. Knowl. Based Syst. 193: 105502 (2020) - [j365]Zhi Li, Chaozhuo Li, Liqun Yang, Philip S. Yu, Zhoujun Li:
Mixture distribution modeling for scalable graph-based semi-supervised learning. Knowl. Based Syst. 200: 105974 (2020) - [j364]Chen Li, Xutan Peng, Shanghang Zhang, Hao Peng, Philip S. Yu, Min He, Linfeng Du, Lihong Wang:
Modeling relation paths for knowledge base completion via joint adversarial training. Knowl. Based Syst. 201-202: 105865 (2020) - [j363]Shao-Heng Ko, Hsu-Chao Lai, Hong-Han Shuai, Wang-Chien Lee, Philip S. Yu, De-Nian Yang:
Optimizing Item and Subgroup Configurations for Social-Aware VR Shopping. Proc. VLDB Endow. 13(8): 1275-1289 (2020) - [j362]Wensheng Gan, Jerry Chun-Wei Lin, Han-Chieh Chao, Athanasios V. Vasilakos, Philip S. Yu:
Utility-Driven Data Analytics on Uncertain Data. IEEE Syst. J. 14(3): 4442-4453 (2020) - [j361]Zhongyuan Jiang, Xianyu Chen, Bowen Dong, Junsan Zhang, Jibing Gong, Hui Yan, Zehua Zhang, Jianfeng Ma, Philip S. Yu:
Trajectory-Based Community Detection. IEEE Trans. Circuits Syst. II Express Briefs 67-II(6): 1139-1143 (2020) - [j360]Zhongyuan Jiang, Jing Li, Jianfeng Ma, Philip S. Yu:
Similarity-Based and Sybil Attack Defended Community Detection for Social Networks. IEEE Trans. Circuits Syst. 67-II(12): 3487-3491 (2020) - [j359]Wensheng Gan, Jerry Chun-Wei Lin, Philippe Fournier-Viger, Han-Chieh Chao, Philip S. Yu:
HUOPM: High-Utility Occupancy Pattern Mining. IEEE Trans. Cybern. 50(3): 1195-1208 (2020) - [j358]Dayong Ye, Tianqing Zhu, Wanlei Zhou, Philip S. Yu:
Differentially Private Malicious Agent Avoidance in Multiagent Advising Learning. IEEE Trans. Cybern. 50(10): 4214-4227 (2020) - [j357]Wensheng Gan, Jerry Chun-Wei Lin, Jiexiong Zhang, Philip S. Yu:
Utility Mining across Multi-Sequences with Individualized Thresholds. Trans. Data Sci. 1(2): 8:1-8:29 (2020) - [j356]Changping Wang, Chaokun Wang, Zheng Wang, Xiaojun Ye, Philip S. Yu:
Edge2vec: Edge-based Social Network Embedding. ACM Trans. Knowl. Discov. Data 14(4): 45:1-45:24 (2020) - [j355]Senzhang Wang, Hao Chen, Jiannong Cao, Jiawei Zhang, Philip S. Yu:
Locally Balanced Inductive Matrix Completion for Demand-Supply Inference in Stationless Bike-Sharing Systems. IEEE Trans. Knowl. Data Eng. 32(12): 2374-2388 (2020) - [j354]Linchuan Xu, Jiannong Cao, Xiaokai Wei, Philip S. Yu:
Network Embedding via Coupled Kernelized Multi-Dimensional Array Factorization. IEEE Trans. Knowl. Data Eng. 32(12): 2414-2425 (2020) - [j353]Wensheng Gan, Jerry Chun-Wei Lin, Han-Chieh Chao, Philippe Fournier-Viger, Xuan Wang, Philip S. Yu:
Utility-Driven Mining of Trend Information for Intelligent System. ACM Trans. Manag. Inf. Syst. 11(3): 14:1-14:28 (2020) - [j352]Yongshan Zhang, Jia Wu, Zhihua Cai, Philip S. Yu:
Multi-View Multi-Label Learning With Sparse Feature Selection for Image Annotation. IEEE Trans. Multim. 22(11): 2844-2857 (2020) - [j351]Jiayu Han, Lei Zheng, Yuanbo Xu, Bangzuo Zhang, Fuzhen Zhuang, Philip S. Yu, Wanli Zuo:
Adaptive Deep Modeling of Users and Items Using Side Information for Recommendation. IEEE Trans. Neural Networks Learn. Syst. 31(3): 737-748 (2020) - [j350]Ling Huang, Chang-Dong Wang, Hongyang Chao, Philip S. Yu:
MVStream: Multiview Data Stream Clustering. IEEE Trans. Neural Networks Learn. Syst. 31(9): 3482-3496 (2020) - [j349]Ning Yang, Yuchi Ma, Li Chen, Philip S. Yu:
A meta-feature based unified framework for both cold-start and warm-start explainable recommendations. World Wide Web 23(1): 241-265 (2020) - [j348]Yue Wang, Chenwei Zhang, Shen Wang, Philip S. Yu, Lu Bai, Lixin Cui, Guandong Xu:
Generative temporal link prediction via self-tokenized sequence modeling. World Wide Web 23(4): 2471-2488 (2020) - [j347]Wenhe Yan, Guiling Li, Zongda Wu, Senzhang Wang, Philip S. Yu:
Extracting diverse-shapelets for early classification on time series. World Wide Web 23(6): 3055-3081 (2020) - [c875]He Huang, Shunta Saito, Yuta Kikuchi, Eiichi Matsumoto, Wei Tang, Philip S. Yu:
Addressing Class Imbalance in Scene Graph Parsing by Learning to Contrast and Score. ACCV (6) 2020: 461-477 - [c874]Qingqin Wang, Yun Xiong, Yangyong Zhu, Philip S. Yu:
KASR: Knowledge-Aware Sequential Recommendation. APWeb/WAIM (1) 2020: 493-508 - [c873]Zhiwei Liu, Xiaohan Li, Ziwei Fan, Stephen D. Guo, Kannan Achan, Philip S. Yu:
Basket Recommendation with Multi-Intent Translation Graph Neural Network. IEEE BigData 2020: 728-737 - [c872]Chen Cui, Ning Yang, Philip S. Yu:
MLANE: Meta-Learning Based Adaptive Network Embedding. IEEE BigData 2020: 904-909 - [c871]Zheng Liu, Xiaohan Li, Hao Peng, Lifang He, Philip S. Yu:
Heterogeneous Similarity Graph Neural Network on Electronic Health Records. IEEE BigData 2020: 1196-1205 - [c870]Shaika Chowdhury, Chenwei Zhang, Philip S. Yu, Yuan Luo:
Med2Meta: Learning Representations of Medical Concepts with Meta-embeddings. HEALTHINF 2020: 369-376 - [c869]He Huang, Wei Tang, Philip S. Yu, Yuanwei Chen, Wenhao Zheng, Qing-Guo Chen:
Multi-label Zero-shot Classification by Learning to Transfer from External Knowledge. BMVC 2020 - [c868]Yingtong Dou, Zhiwei Liu, Li Sun, Yutong Deng, Hao Peng, Philip S. Yu:
Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters. CIKM 2020: 315-324 - [c867]Congying Xia, Chenwei Zhang, Jiawei Zhang, Tingting Liang, Hao Peng, Philip S. Yu:
Low-shot Learning in Natural Language Processing. CogMI 2020: 185-189 - [c866]Tao Zhang, Congying Xia, Chun-Ta Lu, Philip S. Yu:
MZET: Memory Augmented Zero-Shot Fine-grained Named Entity Typing. COLING 2020: 77-87 - [c865]Hu Xu, Lei Shu, Philip S. Yu, Bing Liu:
Understanding Pre-trained BERT for Aspect-based Sentiment Analysis. COLING 2020: 244-250 - [c864]Lichao Sun, Congying Xia, Wenpeng Yin, Tingting Liang, Philip S. Yu, Lifang He:
Mixup-Transformer: Dynamic Data Augmentation for NLP Tasks. COLING 2020: 3436-3440 - [c863]Hu Xu, Seungwhan Moon, Honglei Liu, Bing Liu, Pararth Shah, Philip S. Yu:
User Memory Reasoning for Conversational Recommendation. COLING 2020: 5288-5308 - [c862]Zhongfen Deng, Hao Peng, Congying Xia, Jianxin Li, Lifang He, Philip S. Yu:
Hierarchical Bi-Directional Self-Attention Networks for Paper Review Rating Recommendation. COLING 2020: 6302-6314 - [c861]Jialin Qiao, Yuyuan Kang, Xiangdong Huang, Lei Rui, Tian Jiang, Jianmin Wang, Philip S. Yu:
Heterogeneous Replicas for Multi-dimensional Data Management. DASFAA (1) 2020: 20-36 - [c860]Yun Xiong, Shaofeng Xu, Keyao Rong, Xinyue Liu, Xiangnan Kong, Shanshan Li, Philip S. Yu, Yangyong Zhu:
Code2Text: Dual Attention Syntax Annotation Networks for Structure-Aware Code Translation. DASFAA (3) 2020: 87-103 - [c859]Jin Li, Zhaohui Peng, Senzhang Wang, Xiaokang Xu, Philip S. Yu, Zhenyun Hao:
Heterogeneous Graph Embedding for Cross-Domain Recommendation Through Adversarial Learning. DASFAA (3) 2020: 507-522 - [c858]Xuan Lin, Kaiqi Zhao, Tong Xiao, Zhe Quan, Zhi-Jie Wang, Philip S. Yu:
DeepGS: Deep Representation Learning of Graphs and Sequences for Drug-Target Binding Affinity Prediction. ECAI 2020: 1301-1308 - [c857]Hoang Nguyen, Chenwei Zhang, Congying Xia, Philip S. Yu:
Semantic Matching and Aggregation Network for Few-shot Intent Detection. EMNLP (Findings) 2020: 1209-1218 - [c856]Hu Xu, Bing Liu, Lei Shu, Philip S. Yu:
DomBERT: Domain-oriented Language Model for Aspect-based Sentiment Analysis. EMNLP (Findings) 2020: 1725-1731 - [c855]Congying Xia, Caiming Xiong, Philip S. Yu, Richard Socher:
Composed Variational Natural Language Generation for Few-shot Intents. EMNLP (Findings) 2020: 3379-3388 - [c854]Xuming Hu, Lijie Wen, Yusong Xu, Chenwei Zhang, Philip S. Yu:
SelfORE: Self-supervised Relational Feature Learning for Open Relation Extraction. EMNLP (1) 2020: 3673-3682 - [c853]Shen Wang, Xiaokai Wei, Cícero Nogueira dos Santos, Zhiguo Wang, Ramesh Nallapati, Andrew O. Arnold, Bing Xiang, Philip S. Yu:
H2KGAT: Hierarchical Hyperbolic Knowledge Graph Attention Network. EMNLP (1) 2020: 4952-4962 - [c852]Jian-Guo Zhang, Kazuma Hashimoto, Wenhao Liu, Chien-Sheng Wu, Yao Wan, Philip S. Yu, Richard Socher, Caiming Xiong:
Discriminative Nearest Neighbor Few-Shot Intent Detection by Transferring Natural Language Inference. EMNLP (1) 2020: 5064-5082 - [c851]Jiawei Zhang, Bowen Dong, Philip S. Yu:
FakeDetector: Effective Fake News Detection with Deep Diffusive Neural Network. ICDE 2020: 1826-1829 - [c850]Zhongyuan Jiang, Lichao Sun, Philip S. Yu, Hui Li, Jianfeng Ma, Yulong Shen:
Target Privacy Preserving for Social Networks. ICDE 2020: 1862-1865 - [c849]Xiaohan Li, Mengqi Zhang, Shu Wu, Zheng Liu, Liang Wang, Philip S. Yu:
Dynamic Graph Collaborative Filtering. ICDM 2020: 322-331 - [c848]Li Sun, Zhongbao Zhang, Jiawei Zhang, Feiyang Wang, Yang Du, Sen Su, Philip S. Yu:
Perfect: A Hyperbolic Embedding for Joint User and Community Alignment. ICDM 2020: 501-510 - [c847]Qingyun Sun, Hao Peng, Jianxin Li, Senzhang Wang, Xiangyu Dong, Liangxuan Zhao, Philip S. Yu, Lifang He:
Pairwise Learning for Name Disambiguation in Large-Scale Heterogeneous Academic Networks. ICDM 2020: 511-520 - [c846]Ying Jin, Yunbo Wang, Mingsheng Long, Jianmin Wang, Philip S. Yu, Jiaguang Sun:
A Multi-Player Minimax Game for Generative Adversarial Networks. ICME 2020: 1-6 - [c845]Zhiyu Yao, Yunbo Wang, Mingsheng Long, Jianmin Wang, Philip S. Yu, Jiaguang Sun:
Multi-Task Learning of Generalizable Representations for Video Action Recognition. ICME 2020: 1-6 - [c844]Nooshin Mojab, Vahid Noroozi, Darvin Yi, Manoj Prabhakar Nallabothula, Abdullah Aleem, Philip S. Yu, Joelle A. Hallak:
Real-World Multi-Domain Data Applications for Generalizations to Clinical Settings. ICMLA 2020: 677-684 - [c843]Yue Wang, Zhuo Xu, Lu Bai, Yao Wan, Lixin Cui, Qian Zhao, Edwin R. Hancock, Philip S. Yu:
Cross-Supervised Joint-Event-Extraction with Heterogeneous Information Networks. ICPR 2020: 278-285 - [c842]Chenwei Zhang, Yaliang Li, Nan Du, Wei Fan, Philip S. Yu:
Entity Synonym Discovery via Multipiece Bilateral Context Matching. IJCAI 2020: 1431-1437 - [c841]Dongxiao He, Lu Zhai, Zhigang Li, Di Jin, Liang Yang, Yuxiao Huang, Philip S. Yu:
Adversarial Mutual Information Learning for Network Embedding. IJCAI 2020: 3321-3327 - [c840]Fanzhen Liu, Shan Xue, Jia Wu, Chuan Zhou, Wenbin Hu, Cécile Paris, Surya Nepal, Jian Yang, Philip S. Yu:
Deep Learning for Community Detection: Progress, Challenges and Opportunities. IJCAI 2020: 4981-4987 - [c839]Yu Lei, Philip S. Yu:
Container Scheduling in Blockchain-based Cloud Service Platform. ISPA/BDCloud/SocialCom/SustainCom 2020: 976-983 - [c838]Yingtong Dou, Guixiang Ma, Philip S. Yu, Sihong Xie:
Robust Spammer Detection by Nash Reinforcement Learning. KDD 2020: 924-933 - [c837]Yao Zhang, Yun Xiong, Yun Ye, Tengfei Liu, Weiqiang Wang, Yangyong Zhu, Philip S. Yu:
SEAL: Learning Heuristics for Community Detection with Generative Adversarial Networks. KDD 2020: 1103-1113 - [c836]Yue He, Peng Cui, Jianxin Ma, Hao Zou, Xiaowei Wang, Hongxia Yang, Philip S. Yu:
Learning Stable Graphs from Multiple Environments with Selection Bias. KDD 2020: 2194-2202 - [c835]Yuwei Cao, Hao Peng, Philip S. Yu:
Multi-information Source HIN for Medical Concept Embedding. PAKDD (2) 2020: 396-408 - [c834]Zhiwei Liu, Mengting Wan, Stephen D. Guo, Kannan Achan, Philip S. Yu:
BasConv: Aggregating Heterogeneous Interactions for Basket Recommendation with Graph Convolutional Neural Network. SDM 2020: 64-72 - [c833]Charu C. Aggarwal, Yao Li, Philip S. Yu:
On Supervised Change Detection in Graph Streams. SDM 2020: 289-297 - [c832]Ye Liu, Tao Yang, Zeyu You, Wei Fan, Philip S. Yu:
Commonsense Evidence Generation and Injection in Reading Comprehension. SIGdial 2020: 61-73 - [c831]Jibing Gong, Shen Wang, Jinlong Wang, Wenzheng Feng, Hao Peng, Jie Tang, Philip S. Yu:
Attentional Graph Convolutional Networks for Knowledge Concept Recommendation in MOOCs in a Heterogeneous View. SIGIR 2020: 79-88 - [c830]Zhiwei Liu, Yingtong Dou, Philip S. Yu, Yutong Deng, Hao Peng:
Alleviating the Inconsistency Problem of Applying Graph Neural Network to Fraud Detection. SIGIR 2020: 1569-1572 - [c829]Tingting Liang, Congying Xia, Yuyu Yin, Philip S. Yu:
Joint Training Capsule Network for Cold Start Recommendation. SIGIR 2020: 1769-1772 - [c828]Shaika Chowdhury, Philip S. Yu, Yuan Luo:
Improving Medical NLI Using Context-Aware Domain Knowledge. *SEM@COLING 2020: 1-11 - [c827]Jian-Guo Zhang, Kazuma Hashimoto, Chien-Sheng Wu, Yao Wan, Philip S. Yu, Richard Socher, Caiming Xiong:
Find or Classify? Dual Strategy for Slot-Value Predictions on Multi-Domain Dialog State Tracking. *SEM@COLING 2020: 154-167 - [c826]Lichao Sun, Albert C. Chen, Philip S. Yu, Wei Chen:
Influence Maximization with Spontaneous User Adoption. WSDM 2020: 573-581 - [e36]Jing He, Philip S. Yu, Yong Shi, Xingsen Li, Zhijun Xie, Guangyan Huang, Jie Cao, Fu Xiao:
Data Science - 6th International Conference, ICDS 2019, Ningbo, China, May 15-20, 2019, Revised Selected Papers. Communications in Computer and Information Science 1179, Springer 2020, ISBN 978-981-15-2809-5 [contents] - [i235]Yuhui Zhao, Ning Yang, Tao Lin, Philip S. Yu:
Deep Collaborative Embedding for information cascade prediction. CoRR abs/2001.06665 (2020) - [i234]Zhiwei Liu, Mengting Wan, Stephen D. Guo, Kannan Achan, Philip S. Yu:
BasConv: Aggregating Heterogeneous Interactions for Basket Recommendation with Graph Convolutional Neural Network. CoRR abs/2001.09900 (2020) - [i233]Huanrui Luo, Ning Yang, Philip S. Yu:
Hybrid Deep Embedding for Recommendations with Dynamic Aspect-Level Explanations. CoRR abs/2001.10341 (2020) - [i232]Shaoxiong Ji, Shirui Pan, Erik Cambria, Pekka Marttinen, Philip S. Yu:
A Survey on Knowledge Graphs: Representation, Acquisition and Applications. CoRR abs/2002.00388 (2020) - [i231]Zhongyuan Jiang, Lichao Sun, Philip S. Yu, Hui Li, Jianfeng Ma, Yulong Shen:
Target Privacy Preserving for Social Networks. CoRR abs/2002.03284 (2020) - [i230]Shao-Heng Ko, Hsu-Chao Lai, Hong-Han Shuai, De-Nian Yang, Wang-Chien Lee, Philip S. Yu:
Optimizing Item and Subgroup Configurations for Social-Aware VR Shopping. CoRR abs/2002.04338 (2020) - [i229]Lichao Sun, Yingbo Zhou, Philip S. Yu, Caiming Xiong:
Differentially Private Deep Learning with Smooth Sensitivity. CoRR abs/2003.00505 (2020) - [i228]Lichao Sun, Kazuma Hashimoto, Wenpeng Yin, Akari Asai, Jia Li, Philip S. Yu, Caiming Xiong:
Adv-BERT: BERT is not robust on misspellings! Generating nature adversarial samples on BERT. CoRR abs/2003.04985 (2020) - [i227]Aoqian Zhang, Shaoxu Song, Jianmin Wang, Philip S. Yu:
Time Series Data Cleaning: From Anomaly Detection to Anomaly Repairing (Technical Report). CoRR abs/2003.12396 (2020) - [i226]Tao Zhang, Congying Xia, Chun-Ta Lu, Philip S. Yu:
MZET: Memory Augmented Zero-Shot Fine-grained Named Entity Typing. CoRR abs/2004.01267 (2020) - [i225]Congying Xia, Chenwei Zhang, Hoang Nguyen, Jiawei Zhang, Philip S. Yu:
CG-BERT: Conditional Text Generation with BERT for Generalized Few-shot Intent Detection. CoRR abs/2004.01881 (2020) - [i224]Xuming Hu, Lijie Wen, Yusong Xu, Chenwei Zhang, Philip S. Yu:
SelfORE: Self-supervised Relational Feature Learning for Open Relation Extraction. CoRR abs/2004.02438 (2020) - [i223]Shoujin Wang, Liang Hu, Yan Wang, Xiangnan He, Quan Z. Sheng, Mehmet A. Orgun, Longbing Cao, Nan Wang, Francesco Ricci, Philip S. Yu:
Graph Learning Approaches to Recommender Systems: A Review. CoRR abs/2004.11718 (2020) - [i222]Hu Xu, Bing Liu, Lei Shu, Philip S. Yu:
DomBERT: Domain-oriented Language Model for Aspect-based Sentiment Analysis. CoRR abs/2004.13816 (2020) - [i221]Zhiwei Liu, Yingtong Dou, Philip S. Yu, Yutong Deng, Hao Peng:
Alleviating the Inconsistency Problem of Applying Graph Neural Network to Fraud Detection. CoRR abs/2005.00625 (2020) - [i220]Ye Liu, Tao Yang, Zeyu You, Wei Fan, Philip S. Yu:
Commonsense Evidence Generation and Injection in Reading Comprehension. CoRR abs/2005.05240 (2020) - [i219]Fanzhen Liu, Shan Xue, Jia Wu, Chuan Zhou, Wenbin Hu, Cécile Paris, Surya Nepal, Jian Yang, Philip S. Yu:
Deep Learning for Community Detection: Progress, Challenges and Opportunities. CoRR abs/2005.08225 (2020) - [i218]Tingting Liang, Congying Xia, Yuyu Yin, Philip S. Yu:
Joint Training Capsule Network for Cold Start Recommendation. CoRR abs/2005.11467 (2020) - [i217]Hu Xu, Seungwhan Moon, Honglei Liu, Bing Liu, Pararth Shah, Bing Liu, Philip S. Yu:
User Memory Reasoning for Conversational Recommendation. CoRR abs/2006.00184 (2020) - [i216]Yingtong Dou, Guixiang Ma, Philip S. Yu, Sihong Xie:
Robust Spammer Detection by Nash Reinforcement Learning. CoRR abs/2006.06069 (2020) - [i215]Chen Li, Xutan Peng, Hao Peng, Jianxin Li, Lihong Wang, Philip S. Yu:
Forming an Electoral College for a Graph: a Heuristic Semi-supervised Learning Framework. CoRR abs/2006.06469 (2020) - [i214]Shen Wang, Jibing Gong, Jinlong Wang, Wenzheng Feng, Hao Peng, Jie Tang, Philip S. Yu:
Attentional Graph Convolutional Networks for Knowledge Concept Recommendation in MOOCs in a Heterogeneous View. CoRR abs/2006.13257 (2020) - [i213]Jianguo Chen, Kenli Li, Zhaolei Zhang, Keqin Li, Philip S. Yu:
A Survey on Applications of Artificial Intelligence in Fighting Against COVID-19. CoRR abs/2007.02202 (2020) - [i212]Di Jin, Zhizhi Yu, Dongxiao He, Carl Yang, Philip S. Yu, Jiawei Han:
GCN for HIN via Implicit Utilization of Attention and Meta-paths. CoRR abs/2007.02643 (2020) - [i211]Zheng Wang, Xiaojun Ye, Chaokun Wang, Jian Cui, Philip S. Yu:
Network Embedding with Completely-imbalanced Labels. CoRR abs/2007.03545 (2020) - [i210]Nooshin Mojab, Vahid Noroozi, Darvin Yi, Manoj Prabhakar Nallabothula, Abdullah Aleem, Philip S. Yu, Joelle A. Hallak:
Real-World Multi-Domain Data Applications for Generalizations to Clinical Settings. CoRR abs/2007.12672 (2020) - [i209]He Huang, Yuanwei Chen, Wei Tang, Wenhao Zheng, Qing-Guo Chen, Yao Hu, Philip S. Yu:
Multi-label Zero-shot Classification by Learning to Transfer from External Knowledge. CoRR abs/2007.15610 (2020) - [i208]Lichao Sun, Jianwei Qian, Xun Chen, Philip S. Yu:
LDP-FL: Practical Private Aggregation in Federated Learning with Local Differential Privacy. CoRR abs/2007.15789 (2020) - [i207]Qian Li, Hao Peng, Jianxin Li, Congying Xia, Renyu Yang, Lichao Sun, Philip S. Yu, Lifang He:
A Survey on Text Classification: From Shallow to Deep Learning. CoRR abs/2008.00364 (2020) - [i206]Tianqing Zhu, Dayong Ye, Wei Wang, Wanlei Zhou, Philip S. Yu:
More Than Privacy: Applying Differential Privacy in Key Areas of Artificial Intelligence. CoRR abs/2008.01916 (2020) - [i205]Ye Liu, Shaika Chowdhury, Chenwei Zhang, Cornelia Caragea, Philip S. Yu:
Interpretable Multi-Step Reasoning with Knowledge Extraction on Complex Healthcare Question Answering. CoRR abs/2008.02434 (2020) - [i204]Hao Peng, Jianxin Li, Zheng Wang, Renyu Yang, Mingzhe Liu, Mingming Zhang, Philip S. Yu, Lifang He:
Lifelong Property Price Prediction: A Case Study for the Toronto Real Estate Market. CoRR abs/2008.05880 (2020) - [i203]Dayong Ye, Tianqing Zhu, Sheng Shen, Wanlei Zhou, Philip S. Yu:
Differentially Private Multi-Agent Planning for Logistic-like Problems. CoRR abs/2008.06832 (2020) - [i202]Yingtong Dou, Zhiwei Liu, Li Sun, Yutong Deng, Hao Peng, Philip S. Yu:
Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters. CoRR abs/2008.08692 (2020) - [i201]Youwei Liang, Dong Huang, Chang-Dong Wang, Philip S. Yu:
Multi-view Graph Learning by Joint Modeling of Consistency and Inconsistency. CoRR abs/2008.10208 (2020) - [i200]Qingyun Sun, Hao Peng, Jianxin Li, Senzhang Wang, Xiangyu Dong, Liangxuan Zhao, Philip S. Yu, Lifang He:
Pairwise Learning for Name Disambiguation in Large-Scale Heterogeneous Academic Networks. CoRR abs/2008.13099 (2020) - [i199]Tao Zhang, Tianqing Zhu, Mengde Han, Jing Li, Wanlei Zhou, Philip S. Yu:
Fairness Constraints in Semi-supervised Learning. CoRR abs/2009.06190 (2020) - [i198]Congying Xia, Caiming Xiong, Philip S. Yu, Richard Socher:
Composed Variational Natural Language Generation for Few-shot Intents. CoRR abs/2009.10056 (2020) - [i197]Tao Zhang, Tianqing Zhu, Jing Li, Mengde Han, Wanlei Zhou, Philip S. Yu:
Fairness in Semi-supervised Learning: Unlabeled Data Help to Reduce Discrimination. CoRR abs/2009.12040 (2020) - [i196]Ye Liu, Yao Wan, Lifang He, Hao Peng, Philip S. Yu:
KG-BART: Knowledge Graph-Augmented BART for Generative Commonsense Reasoning. CoRR abs/2009.12677 (2020) - [i195]He Huang, Shunta Saito, Yuta Kikuchi, Eiichi Matsumoto, Wei Tang, Philip S. Yu:
Addressing Class Imbalance in Scene Graph Parsing by Learning to Contrast and Score. CoRR abs/2009.13331 (2020) - [i194]Lichao Sun, Congying Xia, Wenpeng Yin, Tingting Liang, Philip S. Yu, Lifang He:
Mixup-Transfomer: Dynamic Data Augmentation for NLP Tasks. CoRR abs/2010.02394 (2020) - [i193]Hoang Nguyen, Chenwei Zhang, Congying Xia, Philip S. Yu:
Dynamic Semantic Matching and Aggregation Network for Few-shot Intent Detection. CoRR abs/2010.02481 (2020) - [i192]Yue Wang, Zhuo Xu, Lu Bai, Yao Wan, Lixin Cui, Qian Zhao, Edwin R. Hancock, Philip S. Yu:
Cross-Supervised Joint-Event-Extraction with Heterogeneous Information Networks. CoRR abs/2010.06310 (2020) - [i191]Zhiwei Liu, Xiaohan Li, Ziwei Fan, Stephen D. Guo, Kannan Achan, Philip S. Yu:
Basket Recommendation with Multi-Intent Translation Graph Neural Network. CoRR abs/2010.11419 (2020) - [i190]Jian-Guo Zhang, Kazuma Hashimoto, Wenhao Liu, Chien-Sheng Wu, Yao Wan, Philip S. Yu, Richard Socher, Caiming Xiong:
Discriminative Nearest Neighbor Few-Shot Intent Detection by Transferring Natural Language Inference. CoRR abs/2010.13009 (2020) - [i189]Chen Cui, Ning Yang, Philip S. Yu:
MLANE: Meta-Learning Based Adaptive Network Embedding. CoRR abs/2010.13023 (2020) - [i188]Xuming Hu, Fukun Ma, Chenyao Liu, Chenwei Zhang, Lijie Wen, Philip S. Yu:
Semi-supervised Relation Extraction via Incremental Meta Self-Training. CoRR abs/2010.16410 (2020) - [i187]Hu Xu, Lei Shu, Philip S. Yu, Bing Liu:
Understanding Pre-trained BERT for Aspect-based Sentiment Analysis. CoRR abs/2011.00169 (2020) - [i186]Zhongfen Deng, Hao Peng, Congying Xia, Jianxin Li, Lifang He, Philip S. Yu:
Hierarchical Bi-Directional Self-Attention Networks for Paper Review Rating Recommendation. CoRR abs/2011.00802 (2020) - [i185]Zhiwei Liu, Lin Meng, Jiawei Zhang, Philip S. Yu:
Deoscillated Graph Collaborative Filtering. CoRR abs/2011.02100 (2020) - [i184]Dayong Ye, Tianqing Zhu, Zishuo Cheng, Wanlei Zhou, Philip S. Yu:
Differential Advising in Multi-Agent Reinforcement Learning. CoRR abs/2011.03640 (2020) - [i183]Chunkai Zhang, Zilin Du, Wensheng Gan, Philip S. Yu:
TKUS: Mining Top-K High-Utility Sequential Patterns. CoRR abs/2011.13454 (2020) - [i182]Chunkai Zhang, Zilin Du, Yuting Yang, Wensheng Gan, Philip S. Yu:
On-shelf Utility Mining of Sequence Data. CoRR abs/2011.13455 (2020) - [i181]Xiao Wang, Deyu Bo, Chuan Shi, Shaohua Fan, Yanfang Ye, Philip S. Yu:
A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources. CoRR abs/2011.14867 (2020) - [i180]Yao Wan, Yang He, Jianguo Zhang, Yulei Sui, Hai Jin, Guandong Xu, Caiming Xiong, Philip S. Yu:
NaturalCC: A Toolkit to Naturalize the Source Code Corpus. CoRR abs/2012.03225 (2020) - [i179]Lingjuan Lyu, Han Yu, Xingjun Ma, Lichao Sun, Jun Zhao, Qiang Yang, Philip S. Yu:
Privacy and Robustness in Federated Learning: Attacks and Defenses. CoRR abs/2012.06337 (2020)
2010 – 2019
- 2019
- [b4]Jiawei Zhang, Philip S. Yu:
Broad Learning Through Fusions - An Application on Social Networks. Springer 2019, ISBN 978-3-030-12527-1, pp. 1-419 - [j346]Yali Gao, Xiaoyong Li, Jirui Li, Yunquan Gao, Philip S. Yu:
Info-Trust: A Multi-Criteria and Adaptive Trustworthiness Calculation Mechanism for Information Sources. IEEE Access 7: 13999-14012 (2019) - [j345]Ke Yu, Lifang He, Philip S. Yu, Wenkai Zhang, Yue Liu:
Coupled Tensor Decomposition for User Clustering in Mobile Internet Traffic Interaction Pattern. IEEE Access 7: 18113-18124 (2019) - [j344]Ling Huang, Chang-Dong Wang, Hong-Yang Chao, Jian-Huang Lai, Philip S. Yu:
A Score Prediction Approach for Optional Course Recommendation via Cross-User-Domain Collaborative Filtering. IEEE Access 7: 19550-19563 (2019) - [j343]Hechang Chen, Bo Yang, Jiming Liu, Xiao-Nong Zhou, Philip S. Yu:
Mining Spatiotemporal Diffusion Network: A New Framework of Active Surveillance Planning. IEEE Access 7: 108458-108473 (2019) - [j342]Yu Lei, Philip S. Yu:
Cloud Service Community Detection for Real-World Service Networks Based on Parallel Graph Computing. IEEE Access 7: 131355-131362 (2019) - [j341]Linchuan Xu, Xiaokai Wei, Jiannong Cao, Philip S. Yu:
Multi-task network embedding. Int. J. Data Sci. Anal. 8(2): 183-198 (2019) - [j340]Jesse Read, Albert Bifet, Wei Fan, Qiang Yang, Philip S. Yu:
Introduction to the special issue on Big Data, IoT Streams and Heterogeneous Source Mining. Int. J. Data Sci. Anal. 8(3): 221-222 (2019) - [j339]Limeng Cui, Jiawei Zhang, Lifang He, Philip S. Yu:
Multi-view collective tensor decomposition for cross-modal hashing. Int. J. Multim. Inf. Retr. 8(1): 47-59 (2019) - [j338]Jianguo Chen, Kenli Li, Huigui Rong, Kashif Bilal, Keqin Li, Philip S. Yu:
A periodicity-based parallel time series prediction algorithm in cloud computing environments. Inf. Sci. 496: 506-537 (2019) - [j337]Jiayu Han, Lei Zheng, He Huang, Yuanbo Xu, Philip S. Yu, Wanli Zuo:
Deep Latent Factor Model with Hierarchical Similarity Measure for recommender systems. Inf. Sci. 503: 521-532 (2019) - [j336]Wensheng Gan, Jerry Chun-Wei Lin, Han-Chieh Chao, Hamido Fujita, Philip S. Yu:
Correlated utility-based pattern mining. Inf. Sci. 504: 470-486 (2019) - [j335]Qianyi Zhan, Jiawei Zhang, Philip S. Yu:
Integrated anchor and social link predictions across multiple social networks. Knowl. Inf. Syst. 60(1): 303-326 (2019) - [j334]Han Zhang, Chang-Dong Wang, Jian-Huang Lai, Philip S. Yu:
Community detection using multilayer edge mixture model. Knowl. Inf. Syst. 60(2): 757-779 (2019) - [j333]Xi Zhang, Yixuan Li, Senzhang Wang, Binxing Fang, Philip S. Yu:
Enhancing stock market prediction with extended coupled hidden Markov model over multi-sourced data. Knowl. Inf. Syst. 61(2): 1071-1090 (2019) - [j332]Chaozhuo Li, Senzhang Wang, Dejian Yang, Philip S. Yu, Yanbo Liang, Zhoujun Li:
Adversarial learning for multi-view network embedding on incomplete graphs. Knowl. Based Syst. 180: 91-103 (2019) - [j331]Yongshan Zhang, Jia Wu, Zhihua Cai, Bo Du, Philip S. Yu:
An unsupervised parameter learning model for RVFL neural network. Neural Networks 112: 85-97 (2019) - [j330]Ahmed A. Metwally, Philip S. Yu, Derek Reiman, Yang Dai, Patricia W. Finn, David L. Perkins:
Utilizing longitudinal microbiome taxonomic profiles to predict food allergy via Long Short-Term Memory networks. PLoS Comput. Biol. 15(2) (2019) - [j329]Zhang-Meng Liu, Philip S. Yu:
Classification, Denoising, and Deinterleaving of Pulse Streams With Recurrent Neural Networks. IEEE Trans. Aerosp. Electron. Syst. 55(4): 1624-1639 (2019) - [j328]Chang-Dong Wang, Zhi-Hong Deng, Jian-Huang Lai, Philip S. Yu:
Serendipitous Recommendation in E-Commerce Using Innovator-Based Collaborative Filtering. IEEE Trans. Cybern. 49(7): 2678-2692 (2019) - [j327]Yongshan Zhang, Jia Wu, Chuan Zhou, Zhihua Cai, Jian Yang, Philip S. Yu:
Multi-View Fusion with Extreme Learning Machine for Clustering. ACM Trans. Intell. Syst. Technol. 10(5): 53:1-53:23 (2019) - [j326]Senzhang Wang, Xiaoming Zhang, Fengxiang Li, Philip S. Yu, Zhiqiu Huang:
Efficient Traffic Estimation With Multi-Sourced Data by Parallel Coupled Hidden Markov Model. IEEE Trans. Intell. Transp. Syst. 20(8): 3010-3023 (2019) - [j325]Zheng Wang, Xiaojun Ye, Chaokun Wang, Philip S. Yu:
Feature Selection via Transferring Knowledge Across Different Classes. ACM Trans. Knowl. Discov. Data 13(2): 22:1-22:29 (2019) - [j324]Wensheng Gan, Jerry Chun-Wei Lin, Philippe Fournier-Viger, Han-Chieh Chao, Philip S. Yu:
A Survey of Parallel Sequential Pattern Mining. ACM Trans. Knowl. Discov. Data 13(3): 25:1-25:34 (2019) - [j323]Chuan Shi, Binbin Hu, Wayne Xin Zhao, Philip S. Yu:
Heterogeneous Information Network Embedding for Recommendation. IEEE Trans. Knowl. Data Eng. 31(2): 357-370 (2019) - [j322]Xi Zhang, Yuan Su, Siyu Qu, Sihong Xie, Binxing Fang, Philip S. Yu:
IAD: Interaction-Aware Diffusion Framework in Social Networks. IEEE Trans. Knowl. Data Eng. 31(7): 1341-1354 (2019) - [j321]Wei Wu, Bin Li, Ling Chen, Chengqi Zhang, Philip S. Yu:
Improved Consistent Weighted Sampling Revisited. IEEE Trans. Knowl. Data Eng. 31(12): 2332-2345 (2019) - [j320]Ji Wang, Weidong Bao, Lei Zheng, Xiaomin Zhu, Philip S. Yu:
An Attention-augmented Deep Architecture for Hard Drive Status Monitoring in Large-scale Storage Systems. ACM Trans. Storage 15(3): 21:1-21:26 (2019) - [j319]Jianguo Chen, Kenli Li, Kashif Bilal, Xu Zhou, Keqin Li, Philip S. Yu:
A Bi-layered Parallel Training Architecture for Large-Scale Convolutional Neural Networks. IEEE Trans. Parallel Distributed Syst. 30(5): 965-976 (2019) - [j318]Chuan Shi, Zhiqiang Zhang, Yugang Ji, Weipeng Wang, Philip S. Yu, Zhiping Shi:
SemRec: a personalized semantic recommendation method based on weighted heterogeneous information networks. World Wide Web 22(1): 153-184 (2019) - [j317]Yunfeng Hou, Ning Yang, Yi Wu, Philip S. Yu:
Explainable recommendation with fusion of aspect information. World Wide Web 22(1): 221-240 (2019) - [c825]Zhi-Hong Deng, Ling Huang, Chang-Dong Wang, Jian-Huang Lai, Philip S. Yu:
DeepCF: A Unified Framework of Representation Learning and Matching Function Learning in Recommender System. AAAI 2019: 61-68 - [c824]Chaozhuo Li, Senzhang Wang, Yukun Wang, Philip S. Yu, Yanbo Liang, Yun Liu, Zhoujun Li:
Adversarial Learning for Weakly-Supervised Social Network Alignment. AAAI 2019: 996-1003 - [c823]Ji Wang, Weidong Bao, Lichao Sun, Xiaomin Zhu, Bokai Cao, Philip S. Yu:
Private Model Compression via Knowledge Distillation. AAAI 2019: 1190-1197 - [c822]Congying Xia, Chenwei Zhang, Tao Yang, Yaliang Li, Nan Du, Xian Wu, Wei Fan, Fenglong Ma, Philip S. Yu:
Multi-grained Named Entity Recognition. ACL (1) 2019: 1430-1440 - [c821]Chenwei Zhang, Yaliang Li, Nan Du, Wei Fan, Philip S. Yu:
Joint Slot Filling and Intent Detection via Capsule Neural Networks. ACL (1) 2019: 5259-5267 - [c820]Acquah Hackman, Yu Huang, Philip S. Yu, Vincent S. Tseng:
Mining Emerging High Utility Itemsets over Streaming Database. ADMA 2019: 3-16 - [c819]Zhaokun Zhang, Ning Yang, Philip S. Yu:
How to Reach: Discovering Multi-resolution Paths on Large Scale Networks. APWeb/WAIM (1) 2019: 281-288 - [c818]Yingtong Dou, Weijian Li, Zhirong Liu, Zhenhua Dong, Jiebo Luo, Philip S. Yu:
Uncovering download fraud activities in mobile app markets. ASONAM 2019: 671-678 - [c817]Zhiwei Liu, Lei Zheng, Jiawei Zhang, Jiayu Han, Philip S. Yu:
JSCN: Joint Spectral Convolutional Network for Cross Domain Recommendation. IEEE BigData 2019: 850-859 - [c816]Huanrui Luo, Ning Yang, Philip S. Yu:
Hybrid Deep Embedding for Recommendations with Dynamic Aspect-Level Explanations. IEEE BigData 2019: 870-879 - [c815]Jian Wen, Zhongbao Zhang, Zichang Yin, Li Sun, Sen Su, Philip S. Yu:
DeepBlue: Bi-layered LSTM for tweet popUlarity Estimation. IEEE BigData 2019: 968-977 - [c814]Bowen Dong, Charu C. Aggarwal, Philip S. Yu:
The Link Regression Problem in Graph Streams. IEEE BigData 2019: 1088-1095 - [c813]Yuwei Fu, Yun Xiong, Philip S. Yu, Tianyi Tao, Yangyong Zhu:
Metapath Enhanced Graph Attention Encoder for HINs Representation Learning. IEEE BigData 2019: 1103-1110 - [c812]Gen Li, Li Sun, Zhongbao Zhang, Pengxin Ji, Sen Su, Philip S. Yu:
MC2: Unsupervised Multiple Social Network Alignment. IEEE BigData 2019: 1151-1156 - [c811]Jiahao Liu, Guixiang Ma, Fei Jiang, Chun-Ta Lu, Philip S. Yu, Ann B. Ragin:
Community-preserving Graph Convolutions for Structural and Functional Joint Embedding of Brain Networks. IEEE BigData 2019: 1163-1168 - [c810]Li Sun, Zhongbao Zhang, Pengxin Ji, Jian Wen, Sen Su, Philip S. Yu:
DNA: Dynamic Social Network Alignment. IEEE BigData 2019: 1224-1231 - [c809]Xiaokai Wei, Zhiwei Liu, Lichao Sun, Philip S. Yu:
Meta-path Reduction with Transition Probability Preserving in Heterogeneous Information Network. IEEE BigData 2019: 1245-1250 - [c808]Jiawei Zhang, Bowen Dong, Philip S. Yu:
Deep Diffusive Neural Network based Fake News Detection from Heterogeneous Social Networks. IEEE BigData 2019: 1259-1266 - [c807]Zhongyuan Jiang, Jianfeng Ma, Philip S. Yu:
Walk2Privacy: Limiting target link privacy disclosure against the adversarial link prediction. IEEE BigData 2019: 1381-1388 - [c806]Wensheng Gan, Jerry Chun-Wei Lin, Han-Chieh Chao, Philip S. Yu:
Utility-Driven Mining of High Utility Episodes. IEEE BigData 2019: 2644-2653 - [c805]Shen Wang, Philip S. Yu:
Heterogeneous Graph Matching Networks: Application to Unknown Malware Detection. IEEE BigData 2019: 5401-5408 - [c804]Xiaomin Wang, Junsan Zhang, Leiquan Wang, Philip S. Yu, Jie Zhu, Haisheng Li:
Video-level Multi-model Fusion for Action Recognition. CIKM 2019: 159-168 - [c803]Chaozhuo Li, Senzhang Wang, Hao Wang, Yanbo Liang, Philip S. Yu, Zhoujun Li, Wei Wang:
Partially Shared Adversarial Learning For Semi-supervised Multi-platform User Identity Linkage. CIKM 2019: 249-258 - [c802]Chaozhuo Li, Lei Zheng, Senzhang Wang, Feiran Huang, Philip S. Yu, Zhoujun Li:
Multi-Hot Compact Network Embedding. CIKM 2019: 459-468 - [c801]Yuanfu Lu, Xiao Wang, Chuan Shi, Philip S. Yu, Yanfang Ye:
Temporal Network Embedding with Micro- and Macro-dynamics. CIKM 2019: 469-478 - [c800]Xiancheng Xie, Yun Xiong, Philip S. Yu, Yangyong Zhu:
EHR Coding with Multi-scale Feature Attention and Structured Knowledge Graph Propagation. CIKM 2019: 649-658 - [c799]Ye Liu, Chenwei Zhang, Xiaohui Yan, Yi Chang, Philip S. Yu:
Generative Question Refinement with Deep Reinforcement Learning in Retrieval-based QA System. CIKM 2019: 1643-1652 - [c798]Hsu-Chao Lai, Hong-Han Shuai, De-Nian Yang, Jiun-Long Huang, Wang-Chien Lee, Philip S. Yu:
Social-Aware VR Configuration Recommendation via Multi-Feedback Coupled Tensor Factorization. CIKM 2019: 1773-1782 - [c797]Guixiang Ma, Nesreen K. Ahmed, Theodore L. Willke, Dipanjan Sengupta, Michael W. Cole, Nicholas B. Turk-Browne, Philip S. Yu:
Deep Graph Similarity Learning for Brain Data Analysis. CIKM 2019: 2743-2751 - [c796]Chuan Shi, Philip S. Yu:
Recent Developments of Deep Heterogeneous Information Network Analysis. CIKM 2019: 2973-2974 - [c795]Lin Meng, Yuxiang Ren, Jiawei Zhang, Fanghua Ye, Philip S. Yu:
Deep Heterogeneous Social Network Alignment. CogMI 2019: 43-52 - [c794]He Huang, Changhu Wang, Philip S. Yu, Chang-Dong Wang:
Generative Dual Adversarial Network for Generalized Zero-Shot Learning. CVPR 2019: 801-810 - [c793]Yunbo Wang, Jianjin Zhang, Hongyu Zhu, Mingsheng Long, Jianmin Wang, Philip S. Yu:
Memory in Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity From Spatiotemporal Dynamics. CVPR 2019: 9154-9162 - [c792]Xiancheng Xie, Yun Xiong, Philip S. Yu, Kangan Li, Suhua Zhang, Yangyong Zhu:
Attention-Based Abnormal-Aware Fusion Network for Radiology Report Generation. DASFAA (3) 2019: 448-452 - [c791]Yuan Su, Xi Zhang, Senzhang Wang, Binxing Fang, Tianle Zhang, Philip S. Yu:
Understanding Information Diffusion via Heterogeneous Information Network Embeddings. DASFAA (1) 2019: 501-516 - [c790]Yun Xiong, Yao Zhang, Hanjie Fu, Wei Wang, Yangyong Zhu, Philip S. Yu:
DynGraphGAN: Dynamic Graph Embedding via Generative Adversarial Networks. DASFAA (1) 2019: 536-552 - [c789]Lei Zheng, Chun-Ta Lu, Lifang He, Sihong Xie, He Huang, Chaozhuo Li, Vahid Noroozi, Bowen Dong, Philip S. Yu:
MARS: Memory Attention-Aware Recommender System. DSAA 2019: 11-20 - [c788]Vahid Noroozi, Sara Bahaadini, Lei Zheng, Sihong Xie, Philip S. Yu:
Virtual Adversarial Training for Semi-supervised Verification Tasks. EUSIPCO 2019: 1-5 - [c787]Rong Kang, Yue Cao, Mingsheng Long, Jianmin Wang, Philip S. Yu:
Maximum-Margin Hamming Hashing. ICCV 2019: 8251-8260 - [c786]Tianqing Zhu, Philip S. Yu:
Applying Differential Privacy Mechanism in Artificial Intelligence. ICDCS 2019: 1601-1609 - [c785]Yue Wang, Yao Wan, Chenwei Zhang, Lu Bai, Lixin Cui, Philip S. Yu:
Competitive Multi-agent Deep Reinforcement Learning with Counterfactual Thinking. ICDM 2019: 1366-1371 - [c784]Hui Yan, Siyu Liu, Philip S. Yu:
From Joint Feature Selection and Self-Representation Learning to Robust Multi-view Subspace Clustering. ICDM 2019: 1414-1419 - [c783]Jianjin Zhang, Yunbo Wang, Mingsheng Long, Jianmin Wang, Philip S. Yu:
Z-Order Recurrent Neural Networks for Video Prediction. ICME 2019: 230-235 - [c782]Vahid Noroozi, Sara Bahaadini, Samira Sheikhi, Nooshin Mojab, Philip S. Yu:
Leveraging Semi-Supervised Learning for Fairness using Neural Networks. ICMLA 2019: 50-55 - [c781]Mehrnaz Najafi, Lifang He, Philip S. Yu:
Outlier-Robust Multi-Aspect Streaming Tensor Completion and Factorization. IJCAI 2019: 3187-3194 - [c780]Hao Peng, Jianxin Li, Qiran Gong, Yangqiu Song, Yuanxing Ning, Kunfeng Lai, Philip S. Yu:
Fine-grained Event Categorization with Heterogeneous Graph Convolutional Networks. IJCAI 2019: 3238-3245 - [c779]Shen Wang, Zhengzhang Chen, Xiao Yu, Ding Li, Jingchao Ni, Lu-An Tang, Jiaping Gui, Zhichun Li, Haifeng Chen, Philip S. Yu:
Heterogeneous Graph Matching Networks for Unknown Malware Detection. IJCAI 2019: 3762-3770 - [c778]Bowen Dong, Charu C. Aggarwal, Philip S. Yu:
Transfer Learning for Network Classification. IJCNN 2019: 1-8 - [c777]Bowen Dong, Jiawei Zhang, Chenwei Zhang, Yang Yang, Philip S. Yu:
Missing Entity Synergistic Completion across Multiple Isomeric Online Knowledge Libraries. IJCNN 2019: 1-8 - [c776]Nooshin Mojab, Vahid Noroozi, Philip S. Yu, Joelle A. Hallak:
Deep Multi-Task Learning for Interpretable Glaucoma Detection. IRI 2019: 167-174 - [c775]Yao Wan, Jingdong Shu, Yulei Sui, Guandong Xu, Zhou Zhao, Jian Wu, Philip S. Yu:
Multi-modal Attention Network Learning for Semantic Source Code Retrieval. ASE 2019: 13-25 - [c774]Jianguo Zhang, Pengcheng Zou, Zhao Li, Yao Wan, Xiuming Pan, Yu Gong, Philip S. Yu:
Multi-Modal Generative Adversarial Network for Short Product Title Generation in Mobile E-Commerce. NAACL-HLT (2) 2019: 64-72 - [c773]Hu Xu, Bing Liu, Lei Shu, Philip S. Yu:
BERT Post-Training for Review Reading Comprehension and Aspect-based Sentiment Analysis. NAACL-HLT (1) 2019: 2324-2335 - [c772]Yugang Ji, Chuan Shi, Fuzhen Zhuang, Philip S. Yu:
Integrating Topic Model and Heterogeneous Information Network for Aspect Mining with Rating Bias. PAKDD (1) 2019: 160-171 - [c771]Shen Wang, Zhengzhang Chen, Ding Li, Zhichun Li, Lu-An Tang, Jingchao Ni, Junghwan Rhee, Haifeng Chen, Philip S. Yu:
Attentional Heterogeneous Graph Neural Network: Application to Program Reidentification. SDM 2019: 693-701 - [c770]Lei Zheng, Ziwei Fan, Chun-Ta Lu, Jiawei Zhang, Philip S. Yu:
Gated Spectral Units: Modeling Co-evolving Patterns for Sequential Recommendation. SIGIR 2019: 1077-1080 - [c769]Lei Zheng, Chaozhuo Li, Chun-Ta Lu, Jiawei Zhang, Philip S. Yu:
Deep Distribution Network: Addressing the Data Sparsity Issue for Top-N Recommendation. SIGIR 2019: 1081-1084 - [c768]Wensheng Gan, Jerry Chun-Wei Lin, Jiexiong Zhang, Han-Chieh Chao, Hamido Fujita, Philip S. Yu:
ProUM: High Utility Sequential Pattern Mining. SMC 2019: 767-773 - [c767]Xiao Wang, Houye Ji, Chuan Shi, Bai Wang, Yanfang Ye, Peng Cui, Philip S. Yu:
Heterogeneous Graph Attention Network. WWW 2019: 2022-2032 - [c766]Hu Xu, Bing Liu, Lei Shu, Philip S. Yu:
Open-world Learning and Application to Product Classification. WWW 2019: 3413-3419 - [i178]Chenwei Zhang, Yaliang Li, Nan Du, Wei Fan, Philip S. Yu:
SynonymNet: Multi-context Bilateral Matching for Entity Synonyms. CoRR abs/1901.00056 (2019) - [i177]Zonghan Wu, Shirui Pan, Fengwen Chen, Guodong Long, Chengqi Zhang, Philip S. Yu:
A Comprehensive Survey on Graph Neural Networks. CoRR abs/1901.00596 (2019) - [i176]Zhi-Hong Deng, Ling Huang, Chang-Dong Wang, Jian-Huang Lai, Philip S. Yu:
DeepCF: A Unified Framework of Representation Learning and Matching Function Learning in Recommender System. CoRR abs/1901.04704 (2019) - [i175]Hu Xu, Bing Liu, Lei Shu, Philip S. Yu:
Review Conversational Reading Comprehension. CoRR abs/1902.00821 (2019) - [i174]Binhang Yuan, Chen Wang, Fei Jiang, Mingsheng Long, Philip S. Yu, Yuan Liu:
WaveletFCNN: A Deep Time Series Classification Model for Wind Turbine Blade Icing Detection. CoRR abs/1902.05625 (2019) - [i173]Wensheng Gan, Jerry Chun-Wei Lin, Jiexiong Zhang, Hongzhi Yin, Philippe Fournier-Viger, Han-Chieh Chao, Philip S. Yu:
Utility Mining Across Multi-Dimensional Sequences. CoRR abs/1902.09582 (2019) - [i172]Wensheng Gan, Jerry Chun-Wei Lin, Philippe Fournier-Viger, Han-Chieh Chao, Philip S. Yu:
Beyond Frequency: Utility Mining with Varied Item-Specific Minimum Utility. CoRR abs/1902.09584 (2019) - [i171]Wensheng Gan, Jerry Chun-Wei Lin, Han-Chieh Chao, Athanasios V. Vasilakos, Philip S. Yu:
Utility-driven Data Analytics on Uncertain Data. CoRR abs/1902.09586 (2019) - [i170]Yunbo Wang, Mingsheng Long, Jianmin Wang, Philip S. Yu:
Spatiotemporal Pyramid Network for Video Action Recognition. CoRR abs/1903.01038 (2019) - [i169]Chaozhuo Li, Senzhang Wang, Philip S. Yu, Zhoujun Li:
Multi-Hot Compact Network Embedding. CoRR abs/1903.03213 (2019) - [i168]Jianping Cao, Senzhang Wang, Danyan Wen, Zhaohui Peng, Philip S. Yu, Fei-Yue Wang:
Mutual Clustering on Comparative Texts via Heterogeneous Information Networks. CoRR abs/1903.03762 (2019) - [i167]Xiao Wang, Houye Ji, Chuan Shi, Bai Wang, Peng Cui, Philip S. Yu, Yanfang Ye:
Heterogeneous Graph Attention Network. CoRR abs/1903.07293 (2019) - [i166]Jianguo Zhang, Pengcheng Zou, Zhao Li, Yao Wan, Xiuming Pan, Yu Gong, Philip S. Yu:
Multi-Modal Generative Adversarial Network for Short Product Title Generation in Mobile E-Commerce. CoRR abs/1904.01735 (2019) - [i165]Hu Xu, Bing Liu, Lei Shu, Philip S. Yu:
BERT Post-Training for Review Reading Comprehension and Aspect-based Sentiment Analysis. CoRR abs/1904.02232 (2019) - [i164]Wensheng Gan, Jerry Chun-Wei Lin, Han-Chieh Chao, Hamido Fujita, Philip S. Yu:
Correlated Utility-based Pattern Mining. CoRR abs/1904.03336 (2019) - [i163]Jianguo Chen, Kenli Li, Qingying Deng, Keqin Li, Philip S. Yu:
Distributed Deep Learning Model for Intelligent Video Surveillance Systems with Edge Computing. CoRR abs/1904.06400 (2019) - [i162]Wensheng Gan, Jerry Chun-Wei Lin, Jiexiong Zhang, Han-Chieh Chao, Hamido Fujita, Philip S. Yu:
ProUM: Projection-based Utility Mining on Sequence Data. CoRR abs/1904.07764 (2019) - [i161]Wensheng Gan, Jerry Chun-Wei Lin, Jiexiong Zhang, Philippe Fournier-Viger, Han-Chieh Chao, Philip S. Yu:
Fast Utility Mining on Complex Sequences. CoRR abs/1904.12248 (2019) - [i160]Shen Wang, Zhengzhang Chen, Jingchao Ni, Xiao Yu, Zhichun Li, Haifeng Chen, Philip S. Yu:
Adversarial Defense Framework for Graph Neural Network. CoRR abs/1905.03679 (2019) - [i159]Jiawei Zhang, Chenwei Zhang, Bowen Dong, Yang Yang, Philip S. Yu:
Missing Movie Synergistic Completion across Multiple Isomeric Online Movie Knowledge Libraries. CoRR abs/1905.06365 (2019) - [i158]Lichao Sun, Albert C. Chen, Philip S. Yu, Wei Chen:
Self-Activation Influence Maximization. CoRR abs/1906.02296 (2019) - [i157]Hao Peng, Jianxin Li, Qiran Gong, Yangqiu Song, Yuanxing Ning, Kunfeng Lai, Philip S. Yu:
Fine-grained Event Categorization with Heterogeneous Graph Convolutional Networks. CoRR abs/1906.04580 (2019) - [i156]Hao Peng, Jianxin Li, Qiran Gong, Senzhang Wang, Lifang He, Bo Li, Lihong Wang, Philip S. Yu:
Hierarchical Taxonomy-Aware and Attentional Graph Capsule RCNNs for Large-Scale Multi-Label Text Classification. CoRR abs/1906.04898 (2019) - [i155]Senzhang Wang, Jiannong Cao, Philip S. Yu:
Deep Learning for Spatio-Temporal Data Mining: A Survey. CoRR abs/1906.04928 (2019) - [i154]Congying Xia, Chenwei Zhang, Tao Yang, Yaliang Li, Nan Du, Xian Wu, Wei Fan, Fenglong Ma, Philip S. Yu:
Multi-Grained Named Entity Recognition. CoRR abs/1906.08449 (2019) - [i153]Yingtong Dou, Weijian Li, Zhirong Liu, Zhenhua Dong, Jiebo Luo, Philip S. Yu:
Uncovering Download Fraud Activities in Mobile App Markets. CoRR abs/1907.03048 (2019) - [i152]Yue Wang, Yao Wan, Chenwei Zhang, Lixin Cui, Lu Bai, Philip S. Yu:
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking. CoRR abs/1908.04573 (2019) - [i151]Ye Liu, Chenwei Zhang, Xiaohui Yan, Yi Chang, Philip S. Yu:
Generative Question Refinement with Deep Reinforcement Learning in Retrieval-based QA System. CoRR abs/1908.05604 (2019) - [i150]Yuanfu Lu, Xiao Wang, Chuan Shi, Philip S. Yu, Yanfang Ye:
Temporal Network Embedding with Micro- and Macro-dynamics. CoRR abs/1909.04246 (2019) - [i149]Chuan Shi, Xiaotian Han, Li Song, Xiao Wang, Senzhang Wang, Junping Du, Philip S. Yu:
Deep Collaborative Filtering with Multi-Aspect Information in Heterogeneous Networks. CoRR abs/1909.06627 (2019) - [i148]Yao Wan, Jingdong Shu, Yulei Sui, Guandong Xu, Zhou Zhao, Jian Wu, Philip S. Yu:
Multi-Modal Attention Network Learning for Semantic Source Code Retrieval. CoRR abs/1909.13516 (2019) - [i147]Jianguo Zhang, Kazuma Hashimoto, Chien-Sheng Wu, Yao Wan, Philip S. Yu, Richard Socher, Caiming Xiong:
Find or Classify? Dual Strategy for Slot-Value Predictions on Multi-Domain Dialog State Tracking. CoRR abs/1910.03544 (2019) - [i146]Shaika Chowdhury, Chenwei Zhang, Philip S. Yu, Yuan Luo:
Mixed Pooling Multi-View Attention Autoencoder for Representation Learning in Healthcare. CoRR abs/1910.06456 (2019) - [i145]Shaika Chowdhury, Chenwei Zhang, Philip S. Yu, Yuan Luo:
Hierarchical Semantic Correspondence Learning for Post-Discharge Patient Mortality Prediction. CoRR abs/1910.06492 (2019) - [i144]Shen Wang, Zhengzhang Chen, Xiao Yu, Ding Li, Jingchao Ni, Lu-An Tang, Jiaping Gui, Zhichun Li, Haifeng Chen, Philip S. Yu:
Heterogeneous Graph Matching Networks. CoRR abs/1910.08074 (2019) - [i143]Zhiwei Liu, Lei Zheng, Jiawei Zhang, Jiayu Han, Philip S. Yu:
JSCN: Joint Spectral Convolutional Network for Cross Domain Recommendation. CoRR abs/1910.08219 (2019) - [i142]Li Sun, Zhongbao Zhang, Pengxin Ji, Jian Wen, Sen Su, Philip S. Yu:
DNA: Dynamic Social Network Alignment. CoRR abs/1911.00067 (2019) - [i141]Hu Xu, Bing Liu, Lei Shu, Philip S. Yu:
A Failure of Aspect Sentiment Classifiers and an Adaptive Re-weighting Solution. CoRR abs/1911.01460 (2019) - [i140]Jiahao Liu, Guixiang Ma, Fei Jiang, Chun-Ta Lu, Philip S. Yu, Ann B. Ragin:
Community-preserving Graph Convolutions for Structural and Functional Joint Embedding of Brain Networks. CoRR abs/1911.03583 (2019) - [i139]Jianguo Chen, Philip S. Yu:
A Domain Adaptive Density Clustering Algorithm for Data with Varying Density Distribution. CoRR abs/1911.10293 (2019) - [i138]Mingtao Lei, Xi Zhang, Lingyang Chu, Zhefeng Wang, Philip S. Yu, Binxing Fang:
Finding Route Hotspots in Large Labeled Networks. CoRR abs/1911.11354 (2019) - [i137]Yue Wang, Chenwei Zhang, Shen Wang, Philip S. Yu, Lu Bai, Lixin Cui, Guandong Xu:
Generative Temporal Link Prediction via Self-tokenized Sequence Modeling. CoRR abs/1911.11486 (2019) - [i136]Shaika Chowdhury, Chenwei Zhang, Philip S. Yu, Yuan Luo:
Med2Meta: Learning Representations of Medical Concepts with Meta-Embeddings. CoRR abs/1912.03366 (2019) - [i135]Guixiang Ma, Nesreen K. Ahmed, Theodore L. Willke, Philip S. Yu:
Deep Graph Similarity Learning: A Survey. CoRR abs/1912.11615 (2019) - [i134]Wensheng Gan, Jerry Chun-Wei Lin, Han-Chieh Chao, Philippe Fournier-Viger, Xuan Wang, Philip S. Yu:
Utility-Driven Mining of Trend Information for Intelligent System. CoRR abs/1912.11666 (2019) - [i133]Wensheng Gan, Jerry Chun-Wei Lin, Han-Chieh Chao, Philip S. Yu:
Discovering High Utility Episodes in Sequences. CoRR abs/1912.11670 (2019) - [i132]Wensheng Gan, Jerry Chun-Wei Lin, Jiexiong Zhang, Philip S. Yu:
Utility Mining Across Multi-Sequences with Individualized Thresholds. CoRR abs/1912.11673 (2019) - [i131]Vahid Noroozi, Sara Bahaadini, Samira Sheikhi, Nooshin Mojab, Philip S. Yu:
Leveraging Semi-Supervised Learning for Fairness using Neural Networks. CoRR abs/1912.13230 (2019) - 2018
- [j316]Taisong Li, Jiawei Zhang, Philip S. Yu, Yan Zhang, Yonghong Yan:
Deep Dynamic Network Embedding for Link Prediction. IEEE Access 6: 29219-29230 (2018) - [j315]Xi Zhang, Siyu Qu, Jieyun Huang, Binxing Fang, Philip S. Yu:
Stock Market Prediction via Multi-Source Multiple Instance Learning. IEEE Access 6: 50720-50728 (2018) - [j314]Xi Zhang, Yunjia Zhang, Senzhang Wang, Yuntao Yao, Binxing Fang, Philip S. Yu:
Improving stock market prediction via heterogeneous information fusion. Knowl. Based Syst. 143: 236-247 (2018) - [j313]Jiawei Zhang, Philip S. Yu:
Broad Learning: : An Emerging Area in Social Network Analysis. SIGKDD Explor. 20(1): 24-50 (2018) - [j312]Hong-Han Shuai, De-Nian Yang, Chih-Ya Shen, Philip S. Yu, Ming-Syan Chen:
QMSampler: Joint Sampling of Multiple Networks with Quality Guarantee. IEEE Trans. Big Data 4(1): 90-104 (2018) - [j311]Weiwei Shi, Yongxin Zhu, Philip S. Yu, Jiawei Zhang, Tian Huang, Chang Wang, Yufeng Chen:
Effective Prediction of Missing Data on Apache Spark over Multivariable Time Series. IEEE Trans. Big Data 4(4): 473-486 (2018) - [j310]Xuebin Ren, Chia-Mu Yu, Weiren Yu, Shusen Yang, Xinyu Yang, Julie A. McCann, Philip S. Yu:
LoPub: High-Dimensional Crowdsourced Data Publication With Local Differential Privacy. IEEE Trans. Inf. Forensics Secur. 13(9): 2151-2166 (2018) - [j309]Changping Wang, Chaokun Wang, Gaoyang Guo, Xiaojun Ye, Philip S. Yu:
Efficient Computation of G-Skyline Groups. IEEE Trans. Knowl. Data Eng. 30(4): 674-688 (2018) - [j308]Hong-Han Shuai, Chih-Ya Shen, De-Nian Yang, Yi-Feng Lan, Wang-Chien Lee, Philip S. Yu, Ming-Syan Chen:
A Comprehensive Study on Social Network Mental Disorders Detection via Online Social Media Mining. IEEE Trans. Knowl. Data Eng. 30(7): 1212-1225 (2018) - [j307]Jia Wu, Shirui Pan, Xingquan Zhu, Chengqi Zhang, Philip S. Yu:
Multiple Structure-View Learning for Graph Classification. IEEE Trans. Neural Networks Learn. Syst. 29(7): 3236-3251 (2018) - [j306]Chuan Shi, Jian Liu, Yiding Zhang, Binbin Hu, Shenghua Liu, Philip S. Yu:
MFPR: A Personalized Ranking Recommendation with Multiple Feedback. ACM Trans. Soc. Comput. 1(2): 7:1-7:22 (2018) - [j305]Yang Yang, Feifei Wang, Junni Zhang, Jin Xu, Philip S. Yu:
A topic model for co-occurring normal documents and short texts. World Wide Web 21(2): 487-513 (2018) - [c765]Ye Liu, Lifang He, Bokai Cao, Philip S. Yu, Ann B. Ragin, Alex D. Leow:
Multi-View Multi-Graph Embedding for Brain Network Clustering Analysis. AAAI 2018: 117-124 - [c764]Hu Xu, Sihong Xie, Lei Shu, Philip S. Yu:
Dual Attention Network for Product Compatibility and Function Satisfiability Analysis. AAAI 2018: 6013-6020 - [c763]Hu Xu, Bing Liu, Lei Shu, Philip S. Yu:
Double Embeddings and CNN-based Sequence Labeling for Aspect Extraction. ACL (2) 2018: 592-598 - [c762]Xiaotian Han, Chuan Shi, Lei Zheng, Philip S. Yu, Jianxin Li, Yuanfu Lu:
Representation Learning with Depth and Breadth for Recommendation Using Multi-view Data. APWeb/WAIM (1) 2018: 181-188 - [c761]Vahid Noroozi, Sara Bahaadini, Lei Zheng, Sihong Xie, Weixiang Shao, Philip S. Yu:
Semi-supervised Deep Representation Learning for Multi-View Problems. IEEE BigData 2018: 56-64 - [c760]Sara Amini, Vahid Noroozi, Sara Bahaadini, Philip S. Yu, Chris Kanich:
DeepFP: A Deep Learning Framework For User Fingerprinting via Mobile Motion Sensors. IEEE BigData 2018: 84-91 - [c759]Shuaijun Ge, Guixiang Ma, Sihong Xie, Philip S. Yu:
Securing Behavior-based Opinion Spam Detection. IEEE BigData 2018: 112-117 - [c758]Yao Wan, Wenqiang Yan, Jianwei Gao, Zhou Zhao, Jian Wu, Philip S. Yu:
Improved Dynamic Memory Network for Dialogue Act Classification with Adversarial Training. IEEE BigData 2018: 841-850 - [c757]Lei Zheng, Yixue Wang, Lifang He, Sihong Xie, Fengjiao Wang, Philip S. Yu:
PER: A Probabilistic Attentional Model for Personalized Text Recommendations. IEEE BigData 2018: 911-920 - [c756]Yue Wang, Chenwei Zhang, Shen Wang, Philip S. Yu, Lu Bai, Lixin Cui:
Market Abnormality Period Detection via Co-movement Attention Model. IEEE BigData 2018: 1514-1523 - [c755]Ye Liu, Jiawei Zhang, Chenwei Zhang, Philip S. Yu:
Data-driven Blockbuster Planning on Online Movie Knowledge Library. IEEE BigData 2018: 1612-1617 - [c754]Wensheng Gan, Jerry Chun-Wei Lin, Han-Chieh Chao, Tzung-Pei Hong, Philip S. Yu:
CoUPM: Correlated Utility-based Pattern Mining. IEEE BigData 2018: 2607-2616 - [c753]Wensheng Gan, Jerry Chun-Wei Lin, Han-Chieh Chao, Shyue-Liang Wang, Philip S. Yu:
Privacy Preserving Utility Mining: A Survey. IEEE BigData 2018: 2617-2626 - [c752]Chaozhuo Li, Senzhang Wang, Philip S. Yu, Lei Zheng, Xiaoming Zhang, Zhoujun Li, Yanbo Liang:
Distribution Distance Minimization for Unsupervised User Identity Linkage. CIKM 2018: 447-456 - [c751]Hong-Han Shuai, Yen-Chieh Lien, De-Nian Yang, Yi-Feng Lan, Wang-Chien Lee, Philip S. Yu:
Newsfeed Filtering and Dissemination for Behavioral Therapy on Social Network Addictions. CIKM 2018: 597-606 - [c750]Liang Chen, Yang Liu, Zibin Zheng, Philip S. Yu:
Heterogeneous Neural Attentive Factorization Machine for Rating Prediction. CIKM 2018: 833-842 - [c749]Sara Amini, Vahid Noroozi, Amit Pande, Satyajit Gupte, Philip S. Yu, Chris Kanich:
DeepAuth: A Framework for Continuous User Re-authentication in Mobile Apps. CIKM 2018: 2027-2035 - [c748]Sihong Xie, Philip S. Yu:
Next Generation Trustworthy Fraud Detection. CIC 2018: 279-282 - [c747]Xinghua Wang, Zhaohui Peng, Senzhang Wang, Philip S. Yu, Wenjing Fu, Xiaoguang Hong:
Cross-Domain Recommendation for Cold-Start Users via Neighborhood Based Feature Mapping. DASFAA (1) 2018: 158-165 - [c746]Congying Xia, Chenwei Zhang, Xiaohui Yan, Yi Chang, Philip S. Yu:
Zero-shot User Intent Detection via Capsule Neural Networks. EMNLP 2018: 3090-3099 - [c745]Zhenhua Zhang, Leon Stenneth, Ram Marappan, Zaba Sebastian, Philip S. Yu:
Insert beyond the traffic sign recognition: constructing an auto-pilot map for autonomous vehicles. SIGSPATIAL/GIS 2018: 468-471 - [c744]Yue Wang, Chenwei Zhang, Shen Wang, Philip S. Yu, Lu Bai, Lixin Cui:
Deep Co-Investment Network Learning for Financial Assets. ICBK 2018: 41-48 - [c743]Lichao Sun, Lifang He, Zhipeng Huang, Bokai Cao, Congying Xia, Xiaokai Wei, Philip S. Yu:
Joint Embedding of Meta-Path and Meta-Graph for Heterogeneous Information Networks. ICBK 2018: 131-138 - [c742]Ji Wang, Bokai Cao, Philip S. Yu, Lichao Sun, Weidong Bao, Xiaomin Zhu:
Deep Learning towards Mobile Applications. ICDCS 2018: 1385-1393 - [c741]Changping Wang, Chaokun Wang, Gaoyang Guo, Xiaojun Ye, Philip S. Yu:
Efficient Computation of G-Skyline Groups (Extended Abstract). ICDE 2018: 1769-1770 - [c740]He Huang, Bokai Cao, Philip S. Yu, Chang-Dong Wang, Alex D. Leow:
dpMood: Exploiting Local and Periodic Typing Dynamics for Personalized Mood Prediction. ICDM 2018: 157-166 - [c739]Chaozhuo Li, Senzhang Wang, Lifang He, Philip S. Yu, Yanbo Liang, Zhoujun Li:
SSDMV: Semi-Supervised Deep Social Spammer Detection by Multi-view Data Fusion. ICDM 2018: 247-256 - [c738]Lifang He, Chun-Ta Lu, Yong Chen, Jiawei Zhang, Linlin Shen, Philip S. Yu, Fei Wang:
A Self-Organizing Tensor Architecture for Multi-view Clustering. ICDM 2018: 1007-1012 - [c737]Fei Jiang, Lei Zheng, Jin Xu, Philip S. Yu:
FI-GRL: Fast Inductive Graph Representation Learning via Projection-Cost Preservation. ICDM 2018: 1067-1072 - [c736]Jianguo Zhang, Ji Wang, Lifang He, Zhao Li, Philip S. Yu:
Layerwise Perturbation-Based Adversarial Training for Hard Drive Health Degree Prediction. ICDM 2018: 1428-1433 - [c735]Limeng Cui, Zhensong Chen, Jiawei Zhang, Lifang He, Yong Shi, Philip S. Yu:
Multi-View Fusion Through Cross-Modal Retrieval. ICIP 2018: 1977-1981 - [c734]Yunbo Wang, Zhifeng Gao, Mingsheng Long, Jianmin Wang, Philip S. Yu:
PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning. ICML 2018: 5110-5119 - [c733]Xiaotian Han, Chuan Shi, Senzhang Wang, Philip S. Yu, Li Song:
Aspect-Level Deep Collaborative Filtering via Heterogeneous Information Networks. IJCAI 2018: 3393-3399 - [c732]Hu Xu, Bing Liu, Lei Shu, Philip S. Yu:
Lifelong Domain Word Embedding via Meta-Learning. IJCAI 2018: 4510-4516 - [c731]Linchuan Xu, Xiaokai Wei, Jiannong Cao, Philip S. Yu:
On Learning Community-specific Similarity Metrics for Cold-start Link Prediction. IJCNN 2018: 1-8 - [c730]Yao Wan, Zhou Zhao, Min Yang, Guandong Xu, Haochao Ying, Jian Wu, Philip S. Yu:
Improving automatic source code summarization via deep reinforcement learning. ASE 2018: 397-407 - [c729]Binbin Hu, Chuan Shi, Wayne Xin Zhao, Philip S. Yu:
Leveraging Meta-path based Context for Top- N Recommendation with A Neural Co-Attention Model. KDD 2018: 1531-1540 - [c728]Xinyue Liu, Xiangnan Kong, Philip S. Yu:
Active Opinion Maximization in Social Networks. KDD 2018: 1840-1849 - [c727]Lichao Sun, Weiran Huang, Philip S. Yu, Wei Chen:
Multi-Round Influence Maximization. KDD 2018: 2249-2258 - [c726]