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ORCIDDi Wang 0015
Person information
- affiliation: King Abdullah University of Science and Technology (KAUST), Saudi Arabia
- affiliation (former): State University of New York at Buffalo, Department of Computer Science and Engineering, USA
Other persons with the same name
- Di Wang — disambiguation page
- Di Wang 0001 — Khalifa University, EBTIC, Abu Dhabi, UAE (and 2 more)
- Di Wang 0002 — Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, Boca Raton, FL, USA
- Di Wang 0003
![[0000-0001-8003-9738]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0001-8003-9738")
— Microsoft Research, Redmond, WA, USA (and 1 more) - Di Wang 0004 — Nanyang Technological University, School of Computer Engineering / Joint NTU-UBC Research Center of Excellence in Active Living for the Elderly, Singapore
- Di Wang 0005 — Google Research, Mountain View, CA, USA (and 1 more)
- Di Wang 0006 — Xi'an Jiaotong University, School of Software Engineering, China (and 1 more)
- Di Wang 0007 — Macquarie University, Department of Computing, Sydney, NSW, Australia (and 1 more)
- Di Wang 0008 — Xi'an Jiaotong University, School of Management, Center for Intelligent Decision-Making and Machine Learning, China (and 2 more)
- Di Wang 0009 — Northeast Petroleum University, School of Electrical Information Engineering, Daqing, China
- Di Wang 0010 — Southeast University, Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology, Nanjing, China
- Di Wang 0011 — Xidian University, School of Computer Science and Technology, Xi'an, China
- Di Wang 0012 — University of Michigan, College of Engineering, Ann Arbor, MI, USA (and 1 more)
- Di Wang 0013 — University of Southampton, Southampton Business School, UK
- Di Wang 0014 — Peking University, Institute of Population Research, Beijing, China
- Di Wang 0016 — Beijing Institute of Technology, China
- Di Wang 0017 — Peking University, Beijing, China (and 1 more)
- Di Wang 0018 — Dalian University of Technology, School of Software Technology, Dalian, Liaoning, China
- Di Wang 0019 — Shanghai Jiao Tong University, School of Mechanical Engineering, Department of Industrial Engineering and Management, Shanghai, China
- Di Wang 0020 — Texas A&M University, Computer Science and Engineering Department, College Station, TX, USA
- Di Wang 0021 — University of Canterbury, Christchurch, New Zealand (and 1 more)
- Di Wang 0022 — Chinese Academy of Agricultural Sciences, Institute of Agricultural Resources and Regional Planning, Beijing, China
- Di Wang 0023 — JD Explore Academy, Beijing, China (and 2 more)
- Di Wang 0024 — Beijing University of Posts and Telecommunications, School of Artificial Intelligence, China (and 1 more)
- Di Wang 0025 — Wuhan University, School of Cyber Science and Engineering, China (and 1 more)
- Di Wang 0026 — Tianjin University, School of Electrical and Information Engineering, China
- Di Wang 0027 — Tianjin University of Science and Technology, School of Electronic Information and Automation, China
- Di Wang 0028 — Plus Inc., Suzhou, China (and 1 more)
- Di Wang 0029 — University of Illinois at Chicago, Department of Mechanical and Industrial Engineering, IL, USA
- Di Wang 0030 — Microsoft Research, Redmond, WA, USA (and 1 more)
- Di Wang 0031 — Facebook, Seattle, WA, USA (and 1 more)
- Di Wang 0032 — University of Macau, State Key Laboratory of Internet of Things for Smart City, Department of Electromachnical Engineering, China
- Di Wang 0033 — Tiangong University, School of Electronics and Information Engineering, Tianjin, China (and 1 more)
- Di Wang 0034 — University of Kitakyushu, Graduate School of Environmental Engineering, Wakamatsu, Japan (and 1 more)
- Di Wang 0035 — Chongqing Jiaotong University, School of Information Science and Engineering, China (and 2 more)
- Di Wang 0036 — Northeast Forestry University, College of Information and Computer Engineering, Harbin, China (and 1 more)
- Di Wang 0037 — Nagoya University, Department of Civil and Environmental Engineering, Japan
- Di Wang 0038 — Wuhan University of Technology, School of Management, China (and 1 more)
- Di Wang 0039 — Northwest Minzu University, Key Laboratory of China's Ethnic Languages and Information Technology of Ministry of Education, Lanzhou, Gansu, China (and 1 more)
- Di Wang 0040 — University of Manchester, School of Informatics, UK (and 1 more)
- Di Wang 0041 — Northeast Petroleum University, Daqing, Heilongjiang, China
- Di Wang 0042 — Institute of Microelectronics, Chinese Academy of Sciences, Beijing, China
- Di Wang 0043 — University of Utah, Salt Lake City, UT, USA
- Di Wang 0044 — Institute for Smart City of Chongqing University in Liyang, Chongqing University, Liyang, China
- Di Wang 0045 — Zhejiang University, Hangzhou, China
- Di Wang 0046 — Nanjing University of Science and Technology, Nanjing, China
- Di Wang 0047 — Ningbo Polytechnic, Ningbo, China
- Di Wang 0048 — Beihang University, Beijing, China
- Di Wang 0049 — University of Science, and Technology, Beijing, China
- Di Wang 0050 — National University of Defense Technology, Changsha, China
- Di Wang 0051 — Qilu University of Technology, Jinan, China
- Di Wang 0052 — Tencent Inc., Hunyuan, Machine Learning Platform Department, Large Language Model Department, China
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2020 – today
- 2025
[j38]Guanghua Liu, Jia Zhang, Peng Lv, Chenlong Wang, Huan Wang, Di Wang:
TAAD: Time-varying adversarial anomaly detection in dynamic graphs. Inf. Process. Manag. 62(1): 103912 (2025)- [j37]Puyu Wang, Yunwen Lei, Di Wang, Yiming Ying, Ding-Xuan Zhou:
Generalization Guarantees of Gradient Descent for Shallow Neural Networks. Neural Comput. 37(2): 344-402 (2025) - [j36]Xin Chen, Junchao Wu, Shu Yang, Runzhe Zhan, Zeyu Wu, Ziyang Luo, Di Wang, Min Yang, Lidia S. Chao, Derek F. Wong:
RepreGuard: Detecting LLM-Generated Text by Revealing Hidden Representation Patterns. Trans. Assoc. Comput. Linguistics 13: 1812-1831 (2025) - [j35]Wen Zhang, Haitao Fu, Huan Wang, Zhiguo Gong, Pan Zhou, Di Wang:
3A Multi-Classification Division-Aggregation Framework for Fake News Detection. IEEE Trans. Big Data 11(1): 130-140 (2025) - [j34]Di Wang, Jinhui Xu:
Private least absolute deviations with heavy-tailed data. Theor. Comput. Sci. 1030: 115071 (2025) - [j33]Yifan Hong, Chuanqi Shi, Junyang Chen, Huan Wang, Di Wang:
Multitask Asynchronous Metalearning for Few-Shot Anomalous Node Detection in Dynamic Networks. IEEE Trans. Comput. Soc. Syst. 12(4): 1890-1901 (2025) - [j32]Shaowei Wang, Jin Li, Changyu Dong, Jin Li, Zhili Zhou, Di Wang, Zikai Wen:
Side-Channel Attacks and New Principles in the Shuffle Model of Differential Privacy. IEEE Trans. Inf. Forensics Secur. 20: 6515-6528 (2025) - [j31]Shaopeng Fu, Di Wang:
Theoretical Analysis of Robust Overfitting for Wide DNNs: An NTK Approach. IEEE Trans. Inf. Theory 71(8): 6311-6339 (2025) - [j30]Lijie Hu, Xinhai Wang, Yixin Liu, Ninghao Liu, Mengdi Huai, Lichao Sun, Di Wang:
Towards Stable and Explainable Attention Mechanisms. IEEE Trans. Knowl. Data Eng. 37(5): 3047-3061 (2025) - [j29]Huan Wang, Junyang Chen, Yirui Wu, Victor C. M. Leung, Di Wang:
EPM: Evolutionary Perception Method for Anomaly Detection in Noisy Dynamic Graphs. IEEE Trans. Knowl. Data Eng. 37(7): 4035-4048 (2025) - [j28]Lijie Hu, Tianhao Huang, Lu Yu, Wanyu Lin, Tianhang Zheng, Di Wang:
Faithful Interpretation for Graph Neural Networks. Trans. Mach. Learn. Res. 2025 (2025) - [j27]Difei Xu, Meng Ding, Zihang Xiang, Jinhui Xu, Di Wang:
Beyond ordinary Lipschitz constraints: Differentially Private optimization with TNC. Trans. Mach. Learn. Res. 2025 (2025) - [c80]Zihao Luo, Xilie Xu, Feng Liu, Yun Sing Koh, Di Wang, Jingfeng Zhang:
Privacy-Preserving Low-Rank Adaptation Against Membership Inference Attacks for Latent Diffusion Models. AAAI 2025: 5883-5891 - [c79]Ruijia Zhang, Mingxi Lei, Meng Ding, Zihang Xiang, Jinhui Xu, Di Wang:
Improved Rates of Differentially Private Nonconvex-Strongly-Concave Minimax Optimization. AAAI 2025: 22524-22532 - [c78]Jia Li, Lijie Hu, Jingfeng Zhang, Tianhang Zheng, Hua Zhang, Di Wang:
Fair Text-to-Image Diffusion via Fair Mapping. AAAI 2025: 26256-26264 - [c77]Keyuan Cheng, Zijian Kan, Zhuoran Zhang, Muhammad Asif Ali, Lijie Hu, Di Wang:
COMPKE: Complex Question Answering under Knowledge Editing. ACL (Findings) 2025: 2557-2576 - [c76]Keyuan Cheng, Xudong Shen, Yihao Yang, TengyueWang TengyueWang, Yang Cao, Muhammad Asif Ali, Hanbin Wang, Lijie Hu, Di Wang:
CODEMENV: Benchmarking Large Language Models on Code Migration. ACL (Findings) 2025: 2719-2744 - [c75]Shu Yang, Shenzhe Zhu, Zeyu Wu, Keyu Wang, Junchi Yao, Junchao Wu, Lijie Hu, Mengdi Li, Derek F. Wong, Di Wang:
Fraud-R1 : A Multi-Round Benchmark for Assessing the Robustness of LLM Against Augmented Fraud and Phishing Inducements. ACL (Findings) 2025: 4374-4420 - [c74]Junchi Yao, Shu Yang, Jianhua Xu, Lijie Hu, Mengdi Li, Di Wang:
Understanding the Repeat Curse in Large Language Models from a Feature Perspective. ACL (Findings) 2025: 7787-7815 - [c73]Muhammad Asif Ali, Nawal Daftardar, Mutayyaba Waheed, Jianbin Qin, Di Wang:
MQA-KEAL: Multi-hop Question Answering under Knowledge Editing for Arabic Language. COLING 2025: 5629-5644 - [c72]Zhuoran Zhang, Yongxiang Li, Zijian Kan, Keyuan Cheng, Lijie Hu, Di Wang:
Locate-then-edit for Multi-hop Factual Recall under Knowledge Editing. ICML 2025 - [c71]Lijie Hu, Chenyang Ren, Zhengyu Hu, Hongbin Lin, Cheng-Long Wang, Zhen Tan, Weimin Lyu, Jingfeng Zhang, Hui Xiong, Di Wang:
Editable Concept Bottleneck Models. ICML 2025 - [c70]Yifan Hong, Muhammad Asif Ali, Huan Wang, Junyang Chen, Di Wang:
ABNet: Mitigating Sample Imbalance in Anomaly Detection Within Dynamic Graphs. IJCAI 2025: 2910-2918 - [c69]Lin Zhang, Lijie Hu, Di Wang:
Mechanistic Unveiling of Transformer Circuits: Self-Influence as a Key to Model Reasoning. NAACL (Findings) 2025: 1387-1404 - [c68]Lijie Hu, Songning Lai, Yuan Hua, Shu Yang, Jingfeng Zhang, Di Wang:
Stable Vision Concept Transformers for Medical Diagnosis. ECML/PKDD (3) 2025: 317-332 - [c67]Xizhi Tian, Meng Ding, Touming Tao, Zihang Xiang, Di Wang:
Differentially Private Sparse Linear Regression with Heavy-Tailed Responses. ECML/PKDD (5) 2025: 363-379 - [c66]Meng Ding, Mingxi Lei, Shaowei Wang, Tianhang Zheng, Di Wang, Jinhui Xu:
Nearly Optimal Differentially Private ReLU Regression. UAI 2025: 1003-1038 - [c65]Zihang Xiang, Tianhao Wang, Di Wang:
Privacy Audit as Bits Transmission: (Im)possibilities for Audit by One Run. USENIX Security Symposium 2025: 2693-2711 - [c64]Shaowei Wang, Changyu Dong, Xiangfu Song, Jin Li, Zhili Zhou, Di Wang, Han Wu:
Beyond Statistical Estimation: Differentially Private Individual Computation via Shuffling. USENIX Security Symposium 2025: 2789-2808 - [c63]Cheng-Long Wang, Qi Li, Zihang Xiang, Yinzhi Cao, Di Wang:
Towards Lifecycle Unlearning Commitment Management: Measuring Sample-level Unlearning Completeness. USENIX Security Symposium 2025: 6481-6500 - [c62]Ruohan Yang, Muhammad Asif Ali, Huan Wang, Junyang Chen, Di Wang:
LUSTER: Link Prediction Utilizing Shared-Latent Space Representation in Multi-Layer Networks. WWW 2025: 2476-2487 - [i136]Jian Chen, Zehui Lin, Wanyu Lin, Wenlong Shi, Xiaoyan Yin, Di Wang:
FedMUA: Exploring the Vulnerabilities of Federated Learning to Malicious Unlearning Attacks. CoRR abs/2501.11848 (2025) - [i135]Chenyang Ren, Huanyi Xie, Shu Yang, Meng Ding, Lijie Hu, Di Wang:
Evaluating Data Influence in Meta Learning. CoRR abs/2501.15963 (2025) - [i134]Zihang Xiang, Tianhao Wang, Di Wang:
Privacy Audit as Bits Transmission: (Im)possibilities for Audit by One Run. CoRR abs/2501.17750 (2025) - [i133]Shaopeng Fu, Liang Ding, Di Wang:
"Short-length" Adversarial Training Helps LLMs Defend "Long-length" Jailbreak Attacks: Theoretical and Empirical Evidence. CoRR abs/2502.04204 (2025) - [i132]Lin Zhang, Wenshuo Dong, Zhuoran Zhang, Shu Yang, Lijie Hu, Ninghao Liu, Pan Zhou, Di Wang:
EAP-GP: Mitigating Saturation Effect in Gradient-based Automated Circuit Identification. CoRR abs/2502.06852 (2025) - [i131]Lin Zhang, Lijie Hu, Di Wang:
Mechanistic Unveiling of Transformer Circuits: Self-Influence as a Key to Model Reasoning. CoRR abs/2502.09022 (2025) - [i130]Shu Yang, Shenzhe Zhu, Zeyu Wu, Keyu Wang, Junchi Yao, Junchao Wu, Lijie Hu, Mengdi Li, Derek F. Wong, Di Wang:
Fraud-R1 : A Multi-Round Benchmark for Assessing the Robustness of LLM Against Augmented Fraud and Phishing Inducements. CoRR abs/2502.12904 (2025) - [i129]Jiaming Zhang, Mingxi Lei, Meng Ding, Mengdi Li, Zihang Xiang, Difei Xu, Jinhui Xu, Di Wang:
Towards User-level Private Reinforcement Learning with Human Feedback. CoRR abs/2502.17515 (2025) - [i128]Tong Li, Shu Yang, Junchao Wu, Jiyao Wei, Lijie Hu, Mengdi Li, Derek F. Wong, Joshua R. Oltmanns, Di Wang:
Can Large Language Models Identify Implicit Suicidal Ideation? An Empirical Evaluation. CoRR abs/2502.17899 (2025) - [i127]Meng Ding, Mingxi Lei, Shaowei Wang, Tianhang Zheng, Di Wang, Jinhui Xu:
Nearly Optimal Differentially Private ReLU Regression. CoRR abs/2503.06009 (2025) - [i126]Lijie Hu, Junchi Liao, Weimin Lyu, Shaopeng Fu, Tianhao Huang, Shu Yang, Guimin Hu, Di Wang:
C2 ATTACK: Towards Representation Backdoor on CLIP via Concept Confusion. CoRR abs/2503.09095 (2025) - [i125]Liangyu Wang, Jie Ren, Hang Xu, Junxiao Wang, Huanyi Xie, David E. Keyes, Di Wang:
ZO2: Scalable Zeroth-Order Fine-Tuning for Extremely Large Language Models with Limited GPU Memory. CoRR abs/2503.12668 (2025) - [i124]Ruijia Zhang, Mingxi Lei, Meng Ding, Zihang Xiang, Jinhui Xu, Di Wang:
Improved Rates of Differentially Private Nonconvex-Strongly-Concave Minimax Optimization. CoRR abs/2503.18317 (2025) - [i123]Shu Yang, Junchao Wu, Xin Chen, Yunze Xiao, Xinyi Yang, Derek F. Wong, Di Wang:
Understanding Aha Moments: from External Observations to Internal Mechanisms. CoRR abs/2504.02956 (2025) - [i122]Junchi Yao, Shu Yang, Jianhua Xu, Lijie Hu, Mengdi Li, Di Wang:
Understanding the Repeat Curse in Large Language Models from a Feature Perspective. CoRR abs/2504.14218 (2025) - [i121]Youming Tao, Zuyuan Zhang, Dongxiao Yu, Xiuzhen Cheng, Falko Dressler, Di Wang:
Second-Order Convergence in Private Stochastic Non-Convex Optimization. CoRR abs/2505.15647 (2025) - [i120]Junchi Yao, Jianhua Xu, Tianyu Xin, Ziyi Wang, Shenzhe Zhu, Shu Yang, Di Wang:
Is Your LLM-Based Multi-Agent a Reliable Real-World Planner? Exploring Fraud Detection in Travel Planning. CoRR abs/2505.16557 (2025) - [i119]Yi Su, Jiayi Zhang, Shu Yang, Xinhai Wang, Lijie Hu, Di Wang:
Understanding How Value Neurons Shape the Generation of Specified Values in LLMs. CoRR abs/2505.17712 (2025) - [i118]Mengdi Li, Jiaye Lin, Xufeng Zhao, Wenhao Lu, Peilin Zhao, Stefan Wermter, Di Wang:
Curriculum-RLAIF: Curriculum Alignment with Reinforcement Learning from AI Feedback. CoRR abs/2505.20075 (2025) - [i117]Wenshuo Dong, Qingsong Yang, Shu Yang, Lijie Hu, Meng Ding, Wanyu Lin, Tianhang Zheng, Di Wang:
Understanding and Mitigating Cross-lingual Privacy Leakage via Language-specific and Universal Privacy Neurons. CoRR abs/2506.00759 (2025) - [i116]Keyuan Cheng, Zijian Kan, Zhixian He, Zhuoran Zhang, Muhammad Asif Ali, Ke Xu, Lijie Hu, Di Wang:
COMPKE: Complex Question Answering under Knowledge Editing. CoRR abs/2506.00829 (2025) - [i115]Keyuan Cheng, Xudong Shen, Yihao Yang, Tengyue Wang, Yang Cao, Muhammad Asif Ali, Hanbin Wang, Lijie Hu, Di Wang:
CODEMENV: Benchmarking Large Language Models on Code Migration. CoRR abs/2506.00894 (2025) - [i114]Lijie Hu, Songning Lai, Yuan Hua, Shu Yang, Jingfeng Zhang, Di Wang:
Stable Vision Concept Transformers for Medical Diagnosis. CoRR abs/2506.05286 (2025) - [i113]Cheng-Long Wang, Qi Li, Zihang Xiang, Yinzhi Cao, Di Wang:
Towards Lifecycle Unlearning Commitment Management: Measuring Sample-level Unlearning Completeness. CoRR abs/2506.06112 (2025) - [i112]Xizhi Tian, Meng Ding, Touming Tao, Zihang Xiang, Di Wang:
Differentially Private Sparse Linear Regression with Heavy-tailed Responses. CoRR abs/2506.06861 (2025) - [i111]Huanyi Xie, Lijie Hu, Lu Yu, Tianhao Huang, Longfei Li, Meng Li, Jun Zhou, Huan Wang, Di Wang:
Efficient Text-Attributed Graph Learning through Selective Annotation and Graph Alignment. CoRR abs/2506.07168 (2025) - [i110]Wenrui Zhou, Shu Yang, Qingsong Yang, Zikun Guo, Lijie Hu, Di Wang:
Flattery in Motion: Benchmarking and Analyzing Sycophancy in Video-LLMs. CoRR abs/2506.07180 (2025) - [i109]Liangliang You, Junchi Yao, Shu Yang, Guimin Hu, Lijie Hu, Di Wang:
Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images. CoRR abs/2506.07184 (2025) - [i108]Xiangxiang Cui, Shu Yang, Tianjin Huang, Wanyu Lin, Lijie Hu, Di Wang:
The Compositional Architecture of Regret in Large Language Models. CoRR abs/2506.15617 (2025) - [i107]Shu Yang, Junchao Wu, Xuansheng Wu, Derek Wong, Ninhao Liu, Di Wang:
Is Long-to-Short a Free Lunch? Investigating Inconsistency and Reasoning Efficiency in LRMs. CoRR abs/2506.19492 (2025) - [i106]Liangyu Wang, Huanyi Xie, Xinhai Wang, Tianjin Huang, Mengdi Li, Di Wang:
Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models. CoRR abs/2506.22950 (2025) - [i105]Liangyu Wang, Junxiao Wang, Jie Ren, Zihang Xiang, David E. Keyes, Di Wang:
FlashDP: Private Training Large Language Models with Efficient DP-SGD. CoRR abs/2507.01154 (2025) - [i104]Liangyu Wang, Huanyi Xie, Di Wang:
DistZO2: High-Throughput and Memory-Efficient Zeroth-Order Fine-tuning LLMs with Distributed Parallel Computing. CoRR abs/2507.03211 (2025) - [i103]Khouloud Saadi, Di Wang:
Task-Based Flexible Feature Distillation for LLMs. CoRR abs/2507.10155 (2025) - [i102]Keyu Wang, Jin Li, Shu Yang, Zhuoran Zhang, Di Wang:
When Truth Is Overridden: Uncovering the Internal Origins of Sycophancy in Large Language Models. CoRR abs/2508.02087 (2025) - [i101]Jiayi Zhang, Shu Yang, Junchao Wu, Derek F. Wong, Di Wang:
Understanding and Mitigating Political Stance Cross-topic Generalization in Large Language Models. CoRR abs/2508.02360 (2025) - [i100]Xinyan Jiang, Lin Zhang, Jiayi Zhang, Qingsong Yang, Guimin Hu, Di Wang, Lijie Hu:
MSRS: Adaptive Multi-Subspace Representation Steering for Attribute Alignment in Large Language Models. CoRR abs/2508.10599 (2025) - [i99]Xin Chen, Junchao Wu, Shu Yang, Runzhe Zhan, Zeyu Wu, Ziyang Luo, Di Wang, Min Yang, Lidia S. Chao, Derek F. Wong:
RepreGuard: Detecting LLM-Generated Text by Revealing Hidden Representation Patterns. CoRR abs/2508.13152 (2025) - [i98]Mengdi Li, Guanqiao Chen, Xufeng Zhao, Haochen Wen, Shu Yang, Di Wang:
PersRM-R1: Enhance Personalized Reward Modeling with Reinforcement Learning. CoRR abs/2508.14076 (2025) - [i97]Difei Xu, Meng Ding, Zihang Xiang, Jinhui Xu, Di Wang:
Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition. CoRR abs/2509.04668 (2025) - [i96]Tiancheng Yang, Lin Zhang, Jiaye Lin, Guimin Hu, Di Wang, Lijie Hu:
D-LEAF: Localizing and Correcting Hallucinations in Multimodal LLMs via Layer-to-head Attention Diagnostics. CoRR abs/2509.07864 (2025) - [i95]Zihang Xiang, Tianhao Wang, Hanshen Xiao, Yuan Tian, Di Wang:
Tight Privacy Audit in One Run. CoRR abs/2509.08704 (2025) - [i94]Zhaoyang Chu, Yao Wan, Zhikun Zhang, Di Wang, Zhou Yang, Hongyu Zhang, Pan Zhou, Xuanhua Shi, Hai Jin, David Lo:
Scrub It Out! Erasing Sensitive Memorization in Code Language Models via Machine Unlearning. CoRR abs/2509.13755 (2025) - [i93]Zikun Guo, Xinyue Xu, Pei Xiang, Shu Yang, Xin Han, Di Wang, Lijie Hu:
Benchmarking and Mitigate Psychological Sycophancy in Medical Vision-Language Models. CoRR abs/2509.21979 (2025) - [i92]Langqi Yang, Tianhang Zheng, Kedong Xiu, Yixuan Chen, Di Wang, Puning Zhao, Zhan Qin, Kui Ren:
HarmMetric Eval: Benchmarking Metrics and Judges for LLM Harmfulness Assessment. CoRR abs/2509.24384 (2025) - [i91]Kedong Xiu, Churui Zeng, Tianhang Zheng, Xinzhe Huang, Xiaojun Jia, Di Wang, Puning Zhao, Zhan Qin, Kui Ren:
Dynamic Target Attack. CoRR abs/2510.02422 (2025) - [i90]Xinzhe Huang, Wenjing Hu, Tianhang Zheng, Kedong Xiu, Xiaojun Jia, Di Wang, Zhan Qin, Kui Ren:
Untargeted Jailbreak Attack. CoRR abs/2510.02999 (2025) - [i89]Zirun Zhou, Zhengyang Xiao, Haochuan Xu, Jing Sun, Di Wang, Jingfeng Zhang:
Goal-oriented Backdoor Attack against Vision-Language-Action Models via Physical Objects. CoRR abs/2510.09269 (2025) - [i88]Xin Chen, Gillian Dobbie, Xinyu Wang, Feng Liu, Di Wang, Jingfeng Zhang:
Robust Learning of Diffusion Models with Extremely Noisy Conditions. CoRR abs/2510.10149 (2025) - [i87]Manjiang Yu, Hongji Li, Priyanka Singh, Xue Li, Di Wang, Lijie Hu:
PIXEL: Adaptive Steering Via Position-wise Injection with eXact Estimated Levels under Subspace Calibration. CoRR abs/2510.10205 (2025) - [i86]Haochuan Xu, Yun Sing Koh, Shuhuai Huang, Zirun Zhou, Di Wang, Jun Sakuma, Jingfeng Zhang:
Model-agnostic Adversarial Attack and Defense for Vision-Language-Action Models. CoRR abs/2510.13237 (2025) - [i85]Xinhai Wang, Shu Yang, Liangyu Wang, Lin Zhang, Huanyi Xie, Lijie Hu, Di Wang:
PAHQ: Accelerating Automated Circuit Discovery through Mixed-Precision Inference Optimization. CoRR abs/2510.23264 (2025) - [i84]Zhuoran Zhang, Tengyue Wang, Xilin Gong, Yang Shi, Haotian Wang, Di Wang, Lijie Hu:
When Modalities Conflict: How Unimodal Reasoning Uncertainty Governs Preference Dynamics in MLLMs. CoRR abs/2511.02243 (2025) - [i83]Shu Yang, Junchao Wu, Xilin Gou, Xuansheng Wu, Derek F. Wong, Ninhao Liu, Di Wang:
Investigating CoT Monitorability in Large Reasoning Models. CoRR abs/2511.08525 (2025) - [i82]Wenqian Ye, Di Wang, Guangtao Zheng, Bohan Liu, Aidong Zhang:
SAGE: Spuriousness-Aware Guided Prompt Exploration for Mitigating Multimodal Bias. CoRR abs/2511.13005 (2025) - [i81]Meng Ding, Mingxi Lei, Shaopeng Fu, Shaowei Wang, Di Wang, Jinhui Xu:
Understanding Private Learning From Feature Perspective. CoRR abs/2511.18006 (2025) - 2024
- [j26]Juexiao Zhou, Longxi Zhou, Di Wang, Xiaopeng Xu, Haoyang Li, Yuetan Chu, Wenkai Han, Xin Gao:
Personalized and privacy-preserving federated heterogeneous medical image analysis with PPPML-HMI. Comput. Biol. Medicine 169: 107861 (2024) - [j25]Yuan Qiu, Jinyan Liu, Di Wang:
Truthful and privacy-preserving generalized linear models. Inf. Comput. 301: 105225 (2024) - [j24]Washim Uddin Mondal, Veni Goyal, Satish V. Ukkusuri, Goutam Das, Di Wang, Mohamed-Slim Alouini, Vaneet Aggarwal:
Near-Perfect Coverage Manifold Estimation in Cellular Networks via Conditional GAN. IEEE Netw. Lett. 6(2): 97-100 (2024) - [j23]Jinyan Su, Jinhui Xu, Di Wang:
PAC learning halfspaces in non-interactive local differential privacy model with public unlabeled data. J. Comput. Syst. Sci. 141: 103496 (2024) - [j22]Jinyan Su, Lijie Hu, Di Wang:
Faster Rates of Differentially Private Stochastic Convex Optimization. J. Mach. Learn. Res. 25: 114:1-114:41 (2024) - [j21]Youming Tao, Cheng-Long Wang, Miao Pan, Dongxiao Yu, Xiuzhen Cheng, Di Wang:
Communication Efficient and Provable Federated Unlearning. Proc. VLDB Endow. 17(5): 1119-1131 (2024) - [j20]Shaowei Wang, Yun Peng, Jin Li, Zikai Wen, Zhipeng Li, Shiyu Yu, Di Wang, Wei Yang:
Privacy Amplification via Shuffling: Unified, Simplified, and Tightened. Proc. VLDB Endow. 17(8): 1870-1883 (2024) - [j19]Di Wang, Jinhui Xu:
Gradient complexity and non-stationary views of differentially private empirical risk minimization. Theor. Comput. Sci. 982: 114259 (2024) - [j18]Junren Chen, Michael K. Ng, Di Wang:
Quantizing Heavy-Tailed Data in Statistical Estimation: (Near) Minimax Rates, Covariate Quantization, and Uniform Recovery. IEEE Trans. Inf. Theory 70(3): 2003-2038 (2024) - [j17]Yidong Wang, Meng Ding, Jinhui Xu, Di Wang:
Fair Single Index Model. ACM Trans. Knowl. Discov. Data 18(9): 233:1-233:33 (2024) - [j16]Lijie Hu, Zihang Xiang, Jiabin Liu, Di Wang:
Nearly Optimal Rates of Privacy-Preserving Sparse Generalized Eigenvalue Problem. IEEE Trans. Knowl. Data Eng. 36(8): 4101-4115 (2024) - [j15]Youming Tao, Shuzhen Chen, Congwei Zhang, Di Wang, Dongxiao Yu, Xiuzhen Cheng, Falko Dressler:
Private Over-the-Air Federated Learning at Band-Limited Edge. IEEE Trans. Mob. Comput. 23(12): 12444-12460 (2024) - [j14]Minghua Wang, Yan Hu, Ziyun Huang, Di Wang, Jinhui Xu:
Persistent Local Homology in Graph Learning. Trans. Mach. Learn. Res. 2024 (2024) - [c61]Jiahuan Pei, Irene Viola, Haochen Huang, Junxiao Wang, Moonisa Ahsan, Fanghua Ye, Yiming Jiang, Yao Sai, Di Wang, Zhumin Chen, Pengjie Ren, Pablo César:
Autonomous Workflow for Multimodal Fine-Grained Training Assistants Towards Mixed Reality. ACL (Findings) 2024: 4051-4066 - [c60]Lijie Hu, Ivan Habernal, Lei Shen, Di Wang:
Differentially Private Natural Language Models: Recent Advances and Future Directions. EACL (Findings) 2024: 478-499 - [c59]Muhammad Ali, Yan Hu, Jianbin Qin, Di Wang:
Antonym vs Synonym Distinction using InterlaCed Encoder NETworks (ICE-NET). EACL (Findings) 2024: 1462-1473 - [c58]Liangyu Wang, Junxiao Wang, Di Wang:
WiP: Towards Light Adaptation of Large Language Models For Personal Hardware. EdgeFM@MobiSys 2024: 30-32 - [c57]Yihuai Hong, Yuelin Zou, Lijie Hu, Ziqian Zeng, Di Wang, Haiqin Yang:
Dissecting Fine-Tuning Unlearning in Large Language Models. EMNLP 2024: 3933-3941 - [c56]Tianhao Huang, Tao Yang, Ivan Habernal, Lijie Hu, Di Wang:
Private Language Models via Truncated Laplacian Mechanism. EMNLP 2024: 3980-3993 - [c55]Shaopeng Fu, Di Wang:
Theoretical Analysis of Robust Overfitting for Wide DNNs: An NTK Approach. ICLR 2024 - [c54]Songning Lai, Lijie Hu, Junxiao Wang, Laure Berti-Équille, Di Wang:
Faithful Vision-Language Interpretation via Concept Bottleneck Models. ICLR 2024 - [c53]Xilie Xu, Keyi Kong, Ning Liu, Lizhen Cui, Di Wang, Jingfeng Zhang, Mohan S. Kankanhalli:
An LLM can Fool Itself: A Prompt-Based Adversarial Attack. ICLR 2024 - [c52]Liyang Zhu, Meng Ding, Vaneet Aggarwal, Jinhui Xu, Di Wang:
Improved Analysis of Sparse Linear Regression in Local Differential Privacy Model. ICLR 2024 - [c51]Meng Ding, Kaiyi Ji, Di Wang, Jinhui Xu:
Understanding Forgetting in Continual Learning with Linear Regression. ICML 2024 - [c50]Mudit Gaur, Amrit S. Bedi, Di Wang, Vaneet Aggarwal:
Closing the Gap: Achieving Global Convergence (Last Iterate) of Actor-Critic under Markovian Sampling with Neural Network Parametrization. ICML 2024 - [c49]Lijie Hu, Yixin Liu, Ninghao Liu, Mengdi Huai, Lichao Sun, Di Wang:
Improving Interpretation Faithfulness for Vision Transformers. ICML 2024 - [c48]Meng Ding, Mingxi Lei, Liyang Zhu, Shaowei Wang, Di Wang, Jinhui Xu:
Revisiting Differentially Private ReLU Regression. NeurIPS 2024 - [c47]Lijie Hu, Songning Lai, Wenshuo Chen, Hongru Xiao, Hongbin Lin, Lu Yu, Jingfeng Zhang, Di Wang:
Towards Multi-dimensional Explanation Alignment for Medical Classification. NeurIPS 2024 - [c46]Keyi Kong, Xilie Xu, Di Wang, Jingfeng Zhang, Mohan S. Kankanhalli:
Perplexity-aware Correction for Robust Alignment with Noisy Preferences. NeurIPS 2024 - [c45]Liyang Zhu, Amina Manseur, Meng Ding, Jinyan Liu, Jinhui Xu, Di Wang:
Truthful High Dimensional Sparse Linear Regression. NeurIPS 2024 - [c44]Zihang Xiang, Tianhao Wang, Di Wang:
Preserving Node-level Privacy in Graph Neural Networks. SP 2024: 4714-4732 - [i80]Muhammad Asif Ali, Yan Hu, Jianbin Qin, Di Wang:
Antonym vs Synonym Distinction using InterlaCed Encoder NETworks (ICE-NET). CoRR abs/2401.10045 (2024) - [i79]Youming Tao, Cheng-Long Wang, Miao Pan, Dongxiao Yu, Xiuzhen Cheng, Di Wang:
Communication Efficient and Provable Federated Unlearning. CoRR abs/2401.11018 (2024) - [i78]Washim Uddin Mondal, Veni Goyal, Satish V. Ukkusuri, Goutam Das, Di Wang, Mohamed-Slim Alouini, Vaneet Aggarwal:
Near-perfect Coverage Manifold Estimation in Cellular Networks via conditional GAN. CoRR abs/2402.06901 (2024) - [i77]Shu Yang, Muhammad Asif Ali, Cheng-Long Wang, Lijie Hu, Di Wang:
MoRAL: MoE Augmented LoRA for LLMs' Lifelong Learning. CoRR abs/2402.11260 (2024) - [i76]Shu Yang, Lijie Hu, Lu Yu, Muhammad Asif Ali, Di Wang:
Human-AI Interactions in the Communication Era: Autophagy Makes Large Models Achieving Local Optima. CoRR abs/2402.11271 (2024) - [i75]Zihao Luo, Xilie Xu, Feng Liu, Yun Sing Koh, Di Wang, Jingfeng Zhang:
Privacy-Preserving Low-Rank Adaptation for Latent Diffusion Models. CoRR abs/2402.11989 (2024) - [i74]Zihang Xiang, Cheng-Long Wang, Di Wang:
How Does Selection Leak Privacy: Revisiting Private Selection and Improved Results for Hyper-parameter Tuning. CoRR abs/2402.13087 (2024) - [i73]Cheng-Long Wang, Qi Li, Zihang Xiang, Di Wang:
Has Approximate Machine Unlearning been evaluated properly? From Auditing to Side Effects. CoRR abs/2403.12830 (2024) - [i72]Shu Yang, Jiayuan Su, Han Jiang, Mengdi Li, Keyuan Cheng, Muhammad Asif Ali, Lijie Hu, Di Wang:
Dialectical Alignment: Resolving the Tension of 3H and Security Threats of LLMs. CoRR abs/2404.00486 (2024) - [i71]Muhammad Asif Ali, Zhengping Li, Shu Yang, Keyuan Cheng, Yang Cao, Tianhao Huang, Lijie Hu, Lu Yu, Di Wang:
PROMPT-SAW: Leveraging Relation-Aware Graphs for Textual Prompt Compression. CoRR abs/2404.00489 (2024) - [i70]Keyuan Cheng, Gang Lin, Haoyang Fei, Yuxuan Zhai, Lu Yu, Muhammad Asif Ali, Lijie Hu, Di Wang:
Multi-hop Question Answering under Temporal Knowledge Editing. CoRR abs/2404.00492 (2024) - [i69]Mudit Gaur, Amrit Singh Bedi, Di Wang, Vaneet Aggarwal:
Closing the Gap: Achieving Global Convergence (Last Iterate) of Actor-Critic under Markovian Sampling with Neural Network Parametrization. CoRR abs/2405.01843 (2024) - [i68]Jiahuan Pei, Irene Viola, Haochen Huang, Junxiao Wang, Moonisa Ahsan, Fanghua Ye, Yiming Jiang, Yao Sai, Di Wang, Zhumin Chen, Pengjie Ren, Pablo César:
Autonomous Workflow for Multimodal Fine-Grained Training Assistants Towards Mixed Reality. CoRR abs/2405.13034 (2024) - [i67]Keyuan Cheng, Muhammad Asif Ali, Shu Yang, Gang Lin, Yuxuan Zhai, Haoyang Fei, Ke Xu, Lu Yu, Lijie Hu, Di Wang:
Leveraging Logical Rules in Knowledge Editing: A Cherry on the Top. CoRR abs/2405.15452 (2024) - [i66]Lijie Hu, Chenyang Ren, Zhengyu Hu, Cheng-Long Wang, Di Wang:
Editable Concept Bottleneck Models. CoRR abs/2405.15476 (2024) - [i65]Meng Ding, Kaiyi Ji, Di Wang, Jinhui Xu:
Understanding Forgetting in Continual Learning with Linear Regression. CoRR abs/2405.17583 (2024) - [i64]Jia Li, Lijie Hu, Zhixian He, Jingfeng Zhang, Tianhang Zheng, Di Wang:
Text Guided Image Editing with Automatic Concept Locating and Forgetting. CoRR abs/2405.19708 (2024) - [i63]Lijie Hu, Liang Liu, Shu Yang, Xin Chen, Hongru Xiao, Mengdi Li, Pan Zhou, Muhammad Asif Ali, Di Wang:
A Hopfieldian View-based Interpretation for Chain-of-Thought Reasoning. CoRR abs/2406.12255 (2024) - [i62]Shaowei Wang, Changyu Dong, Di Wang, Xiangfu Song:
Beyond Statistical Estimation: Differentially Private Individual Computation in the Shuffle Model. CoRR abs/2406.18145 (2024) - [i61]Lijie Hu, Tianhao Huang, Huanyi Xie, Chenyang Ren, Zhengyu Hu, Lu Yu, Di Wang:
Semi-supervised Concept Bottleneck Models. CoRR abs/2406.18992 (2024) - [i60]Binhao Ma, Tianhang Zheng, Hongsheng Hu, Di Wang, Shuo Wang, Zhongjie Ba, Zhan Qin, Kui Ren:
Releasing Malevolence from Benevolence: The Menace of Benign Data on Machine Unlearning. CoRR abs/2407.05112 (2024) - [i59]Xiaochuan Gou, Ziyue Li, Tian Lan, Junpeng Lin, Zhishuai Li, Bingyu Zhao, Chen Zhang, Di Wang, Xiangliang Zhang:
XTraffic: A Dataset Where Traffic Meets Incidents with Explainability and More. CoRR abs/2407.11477 (2024) - [i58]Shaopeng Fu, Xuexue Sun, Ke Qing, Tianhang Zheng, Di Wang:
Pre-trained Encoder Inference: Revealing Upstream Encoders In Downstream Machine Learning Services. CoRR abs/2408.02814 (2024) - [i57]Muhammad Asif Ali, Nawal Daftardar, Mutayyaba Waheed, Jianbin Qin, Di Wang:
MQA-KEAL: Multi-hop Question Answering under Knowledge Editing for Arabic Language. CoRR abs/2409.12257 (2024) - [i56]Lijie Hu, Liang Liu, Shu Yang, Xin Chen, Zhen Tan, Muhammad Asif Ali, Mengdi Li, Di Wang:
Understanding Reasoning in Chain-of-Thought from the Hopfieldian View. CoRR abs/2410.03595 (2024) - [i55]Zhuoran Zhang, Yongxiang Li, Zijian Kan, Keyuan Cheng, Lijie Hu, Di Wang:
Locate-then-edit for Multi-hop Factual Recall under Knowledge Editing. CoRR abs/2410.06331 (2024) - [i54]Yihuai Hong, Yuelin Zou, Lijie Hu, Ziqian Zeng, Di Wang, Haiqin Yang:
Dissecting Fine-Tuning Unlearning in Large Language Models. CoRR abs/2410.06606 (2024) - [i53]Lijie Hu, Tianhao Huang, Lu Yu, Wanyu Lin, Tianhang Zheng, Di Wang:
Faithful Interpretation for Graph Neural Networks. CoRR abs/2410.06950 (2024) - [i52]Tianhao Huang, Tao Yang, Ivan Habernal, Lijie Hu, Di Wang:
Private Language Models via Truncated Laplacian Mechanism. CoRR abs/2410.08027 (2024) - [i51]Shu Yang, Shenzhe Zhu, Ruoxuan Bao, Liang Liu, Yu Cheng, Lijie Hu, Mengdi Li, Di Wang:
What makes your model a low-empathy or warmth person: Exploring the Origins of Personality in LLMs. CoRR abs/2410.10863 (2024) - [i50]Liyang Zhu, Amina Manseur, Meng Ding, Jinyan Liu, Jinhui Xu, Di Wang:
Truthful High Dimensional Sparse Linear Regression. CoRR abs/2410.13046 (2024) - [i49]Lijie Hu, Songning Lai, Wenshuo Chen, Hongru Xiao, Hongbin Lin, Lu Yu, Jingfeng Zhang, Di Wang:
Towards Multi-dimensional Explanation Alignment for Medical Classification. CoRR abs/2410.21494 (2024) - [i48]Lijie Hu, Chenyang Ren, Huanyi Xie, Khouloud Saadi, Shu Yang, Jingfeng Zhang, Di Wang:
Dissecting Misalignment of Multimodal Large Language Models via Influence Function. CoRR abs/2411.11667 (2024) - [i47]Zhi Luo, Xiyuan Yang, Pan Zhou, Di Wang:
Provably Efficient Action-Manipulation Attack Against Continuous Reinforcement Learning. CoRR abs/2411.13116 (2024) - [i46]Qi Li, Cheng-Long Wang, Yinzhi Cao, Di Wang:
Data Lineage Inference: Uncovering Privacy Vulnerabilities of Dataset Pruning. CoRR abs/2411.15796 (2024) - 2023
- [j13]Di Wang, Lijie Hu, Huanyu Zhang, Marco Gaboardi, Jinhui Xu:
Generalized Linear Models in Non-interactive Local Differential Privacy with Public Data. J. Mach. Learn. Res. 24: 132:1-132:57 (2023) - [j12]Zihang Xiang, Tianhao Wang, Wanyu Lin, Di Wang:
Practical Differentially Private and Byzantine-resilient Federated Learning. Proc. ACM Manag. Data 1(2): 119:1-119:26 (2023) - [j11]Junren Chen, Cheng-Long Wang, Michael K. P. Ng, Di Wang:
High Dimensional Statistical Estimation Under Uniformly Dithered One-Bit Quantization. IEEE Trans. Inf. Theory 69(8): 5151-5187 (2023) - [c43]Lijie Hu, Yixin Liu, Ninghao Liu, Mengdi Huai, Lichao Sun, Di Wang:
SEAT: Stable and Explainable Attention. AAAI 2023: 12907-12915 - [c42]Lijie Hu, Zihang Xiang, Jiabin Liu, Di Wang:
Privacy-preserving Sparse Generalized Eigenvalue Problem. AISTATS 2023: 5052-5062 - [c41]Di Wang, Jiahao Ding, Lijie Hu, Zejun Xie, Miao Pan, Jinhui Xu:
Finite Sample Guarantees of Differentially Private Expectation Maximization Algorithm. ECAI 2023: 2435-2442 - [c40]Muhammad Asif Ali, Yan Hu, Jianbin Qin, Di Wang:
GRI: Graph-based Relative Isomorphism of Word Embedding Spaces. EMNLP (Findings) 2023: 11304-11313 - [c39]Jinyan Su, Terry Yue Zhuo, Di Wang, Preslav Nakov:
DetectLLM: Leveraging Log Rank Information for Zero-Shot Detection of Machine-Generated Text. EMNLP (Findings) 2023: 12395-12412 - [c38]Xiaochuan Gou, Lijie Hu, Di Wang, Xiangliang Zhang:
A Fundamental Model with Stable Interpretability for Traffic Forecasting. GeoPrivacy@SIGSPATIAL 2023: 10-13 - [c37]Yulian Wu, Xingyu Zhou, Sayak Ray Chowdhury, Di Wang:
Differentially Private Episodic Reinforcement Learning with Heavy-tailed Rewards. ICML 2023: 37880-37918 - [c36]Rui Chen, Qiyu Wan, Xinyue Zhang, Xiaoqi Qin, Yanzhao Hou, Di Wang, Xin Fu, Miao Pan:
EEFL: High-Speed Wireless Communications Inspired Energy Efficient Federated Learning over Mobile Devices. MobiSys 2023: 544-556 - [c35]Yulian Wu, Xingyu Zhou, Youming Tao, Di Wang:
On Private and Robust Bandits. NeurIPS 2023 - [c34]Hanshen Xiao, Zihang Xiang, Di Wang, Srinivas Devadas:
A Theory to Instruct Differentially-Private Learning via Clipping Bias Reduction. SP 2023: 2170-2189 - [c33]Jinyan Su, Changhong Zhao, Di Wang:
Differentially Private Stochastic Convex Optimization in (Non)-Euclidean Space Revisited. UAI 2023: 2026-2035 - [c32]Cheng-Long Wang, Mengdi Huai, Di Wang:
Inductive Graph Unlearning. USENIX Security Symposium 2023: 3205-3222 - [c31]Muhammad Asif Ali, Maha Alshmrani, Jianbin Qin, Yan Hu, Di Wang:
GARI: Graph Attention for Relative Isomorphism of Arabic Word Embeddings. ArabicNLP 2023: 181-190 - [i45]Lijie Hu, Ivan Habernal, Lei Shen, Di Wang:
Differentially Private Natural Language Models: Recent Advances and Future Directions. CoRR abs/2301.09112 (2023) - [i44]Yulian Wu, Chaowen Guan, Vaneet Aggarwal, Di Wang:
Quantum Heavy-tailed Bandits. CoRR abs/2301.09680 (2023) - [i43]Yulian Wu, Xingyu Zhou, Youming Tao, Di Wang:
On Private and Robust Bandits. CoRR abs/2302.02526 (2023) - [i42]Bhargav Ganguly, Yulian Wu, Di Wang, Vaneet Aggarwal:
Quantum Computing Provides Exponential Regret Improvement in Episodic Reinforcement Learning. CoRR abs/2302.08617 (2023) - [i41]Juexiao Zhou, Longxi Zhou, Di Wang, Xiaopeng Xu, Haoyang Li, Yuetan Chu, Wenkai Han, Xin Gao:
Personalized and privacy-preserving federated heterogeneous medical image analysis with PPPML-HMI. CoRR abs/2302.11571 (2023) - [i40]Jinyan Su, Changhong Zhao, Di Wang:
Differentially Private Stochastic Convex Optimization in (Non)-Euclidean Space Revisited. CoRR abs/2303.18047 (2023) - [i39]Cheng-Long Wang, Mengdi Huai, Di Wang:
Inductive Graph Unlearning. CoRR abs/2304.03093 (2023) - [i38]Zihang Xiang, Tianhao Wang, Wanyu Lin, Di Wang:
Practical Differentially Private and Byzantine-resilient Federated Learning. CoRR abs/2304.09762 (2023) - [i37]Puyu Wang, Yunwen Lei, Di Wang, Yiming Ying, Ding-Xuan Zhou:
Generalization Guarantees of Gradient Descent for Multi-Layer Neural Networks. CoRR abs/2305.16891 (2023) - [i36]Yulian Wu, Xingyu Zhou, Sayak Ray Chowdhury, Di Wang:
Differentially Private Episodic Reinforcement Learning with Heavy-tailed Rewards. CoRR abs/2306.01121 (2023) - [i35]Jinyan Su, Terry Yue Zhuo, Di Wang, Preslav Nakov:
DetectLLM: Leveraging Log Rank Information for Zero-Shot Detection of Machine-Generated Text. CoRR abs/2306.05540 (2023) - [i34]Mudit Gaur, Amrit Singh Bedi, Di Wang, Vaneet Aggarwal:
On the Global Convergence of Natural Actor-Critic with Two-layer Neural Network Parametrization. CoRR abs/2306.10486 (2023) - [i33]Jinyan Su, Terry Yue Zhuo, Jonibek Mansurov, Di Wang, Preslav Nakov:
Fake News Detectors are Biased against Texts Generated by Large Language Models. CoRR abs/2309.08674 (2023) - [i32]Shaopeng Fu, Di Wang:
Theoretical Analysis of Robust Overfitting for Wide DNNs: An NTK Approach. CoRR abs/2310.06112 (2023) - [i31]Liyang Zhu, Meng Ding, Vaneet Aggarwal, Jinhui Xu, Di Wang:
Improved Analysis of Sparse Linear Regression in Local Differential Privacy Model. CoRR abs/2310.07367 (2023) - [i30]Hanpu Shen, Cheng-Long Wang, Zihang Xiang, Yiming Ying, Di Wang:
Differentially Private Non-convex Learning for Multi-layer Neural Networks. CoRR abs/2310.08425 (2023) - [i29]Muhammad Asif Ali, Yan Hu, Jianbin Qin, Di Wang:
GRI: Graph-based Relative Isomorphism of Word Embedding Spaces. CoRR abs/2310.12360 (2023) - [i28]Muhammad Asif Ali, Maha Alshmrani, Jianbin Qin, Yan Hu, Di Wang:
GARI: Graph Attention for Relative Isomorphism of Arabic Word Embeddings. CoRR abs/2310.13068 (2023) - [i27]Xilie Xu, Keyi Kong, Ning Liu, Lizhen Cui, Di Wang, Jingfeng Zhang, Mohan S. Kankanhalli:
An LLM can Fool Itself: A Prompt-Based Adversarial Attack. CoRR abs/2310.13345 (2023) - [i26]Zihang Xiang, Tianhao Wang, Di Wang:
Preserving Node-level Privacy in Graph Neural Networks. CoRR abs/2311.06888 (2023) - [i25]Jia Li, Lijie Hu, Jingfeng Zhang, Tianhang Zheng, Hua Zhang, Di Wang:
Fair Text-to-Image Diffusion via Fair Mapping. CoRR abs/2311.17695 (2023) - [i24]Lijie Hu, Yixin Liu, Ninghao Liu, Mengdi Huai, Lichao Sun, Di Wang:
Improving Faithfulness for Vision Transformers. CoRR abs/2311.17983 (2023) - 2022
- [c30]Jinyan Su, Jinhui Xu, Di Wang:
On PAC Learning Halfspaces in Non-interactive Local Privacy Model with Public Unlabeled Data. ACML 2022: 927-941 - [c29]Youming Tao, Yulian Wu, Peng Zhao, Di Wang:
Optimal Rates of (Locally) Differentially Private Heavy-tailed Multi-Armed Bandits. AISTATS 2022: 1546-1574 - [c28]Vincent Cohen-Addad, Yunus Esencayi, Chenglin Fan, Marco Gaboardi, Shi Li, Di Wang:
On Facility Location Problem in the Local Differential Privacy Model. AISTATS 2022: 3914-3929 - [c27]Jinyan Su, Lijie Hu, Di Wang:
Faster Rates of Private Stochastic Convex Optimization. ALT 2022: 995-1002 - [c26]Youming Tao, Yulian Wu, Xiuzhen Cheng, Di Wang:
Private Stochastic Convex Optimization and Sparse Learning with Heavy-tailed Data Revisited. IJCAI 2022: 3947-3953 - [c25]Di Wang, Jinhui Xu:
Differentially Private ℓ1-norm Linear Regression with Heavy-tailed Data. ISIT 2022: 1856-1861 - [c24]Lijie Hu, Shuo Ni, Hanshen Xiao, Di Wang:
High Dimensional Differentially Private Stochastic Optimization with Heavy-tailed Data. PODS 2022: 227-236 - [c23]Yuan Qiu, Jinyan Liu, Di Wang:
Truthful Generalized Linear Models. WINE 2022: 369-370 - [i23]Di Wang, Jinhui Xu:
Differentially Private 𝓁1-norm Linear Regression with Heavy-tailed Data. CoRR abs/2201.03204 (2022) - [i22]Junren Chen, Cheng-Long Wang, Michael K. Ng, Di Wang:
High Dimensional Statistical Estimation under One-bit Quantization. CoRR abs/2202.13157 (2022) - [i21]Yuan Qiu, Jinyan Liu, Di Wang:
Truthful Generalized Linear Models. CoRR abs/2209.07815 (2022) - [i20]Jinyan Su, Jinhui Xu, Di Wang:
On PAC Learning Halfspaces in Non-interactive Local Privacy Model with Public Unlabeled Data. CoRR abs/2209.08319 (2022) - [i19]Hao Wang, Wanyu Lin, Hao He, Di Wang, Chengzhi Mao, Muhan Zhang:
1st ICLR International Workshop on Privacy, Accountability, Interpretability, Robustness, Reasoning on Structured Data (PAIR^2Struct). CoRR abs/2210.03612 (2022) - [i18]Lijie Hu, Yixin Liu, Ninghao Liu, Mengdi Huai, Lichao Sun, Di Wang:
SEAT: Stable and Explainable Attention. CoRR abs/2211.13290 (2022) - [i17]Junren Chen, Michael Kwok-Po Ng, Di Wang:
Quantizing Heavy-tailed Data in Statistical Estimation: (Near) Minimax Rates, Covariate Quantization, and Uniform Recovery. CoRR abs/2212.14562 (2022) - 2021
- [j10]Di Wang, Jinhui Xu:
Inferring ground truth from crowdsourced data under local attribute differential privacy. Theor. Comput. Sci. 865: 85-98 (2021) - [j9]Di Wang, Jinhui Xu:
Differentially private high dimensional sparse covariance matrix estimation. Theor. Comput. Sci. 865: 119-130 (2021) - [j8]Di Wang, Jinhui Xu:
On Sparse Linear Regression in the Local Differential Privacy Model. IEEE Trans. Inf. Theory 67(2): 1182-1200 (2021) - [c22]Di Wang, Huangyu Zhang, Marco Gaboardi, Jinhui Xu:
Estimating Smooth GLM in Non-interactive Local Differential Privacy Model with Public Unlabeled Data. ALT 2021: 1207-1213 - [c21]Zhiyu Xue, Shaoyang Yang, Mengdi Huai, Di Wang:
Differentially Private Pairwise Learning Revisited. IJCAI 2021: 3242-3248 - [i16]Youming Tao, Yulian Wu, Peng Zhao, Di Wang:
Optimal Rates of (Locally) Differentially Private Heavy-tailed Multi-Armed Bandits. CoRR abs/2106.02575 (2021) - [i15]Lijie Hu, Shuo Ni, Hanshen Xiao, Di Wang:
High Dimensional Differentially Private Stochastic Optimization with Heavy-tailed Data. CoRR abs/2107.11136 (2021) - [i14]Jinyan Su, Di Wang:
Faster Rates of Differentially Private Stochastic Convex Optimization. CoRR abs/2108.00331 (2021) - 2020
- [b1]Di Wang:
Some Fundamental Machine Learning Problems in the Differential Privacy Model. University at Buffalo, New York, USA, 2020 - [j7]Di Wang, Xiangyu Guo, Chaowen Guan, Shi Li, Jinhui Xu:
Estimating stochastic linear combination of non-linear regressions efficiently and scalably. Neurocomputing 399: 129-140 (2020) - [j6]Hongjiang Lei, Di Wang, Ki-Hong Park, Imran Shafique Ansari, Jing Jiang, Gaofeng Pan, Mohamed-Slim Alouini:
Safeguarding UAV IoT Communication Systems Against Randomly Located Eavesdroppers. IEEE Internet Things J. 7(2): 1230-1244 (2020) - [j5]Di Wang, Marco Gaboardi, Adam D. Smith, Jinhui Xu:
Empirical Risk Minimization in the Non-interactive Local Model of Differential Privacy. J. Mach. Learn. Res. 21: 200:1-200:39 (2020) - [j4]Di Wang, Xiangyu Guo, Shi Li, Jinhui Xu:
Robust high dimensional expectation maximization algorithm via trimmed hard thresholding. Mach. Learn. 109(12): 2283-2311 (2020) - [j3]Di Wang, Jinhui Xu:
Principal Component Analysis in the local differential privacy model. Theor. Comput. Sci. 809: 296-312 (2020) - [j2]Di Wang, Jinhui Xu:
Tight lower bound of sparse covariance matrix estimation in the local differential privacy model. Theor. Comput. Sci. 815: 47-59 (2020) - [c20]Mengdi Huai, Di Wang, Chenglin Miao, Jinhui Xu, Aidong Zhang:
Pairwise Learning with Differential Privacy Guarantees. AAAI 2020: 694-701 - [c19]Mengdi Huai, Di Wang, Chenglin Miao, Aidong Zhang:
Towards Interpretation of Pairwise Learning. AAAI 2020: 4166-4173 - [c18]Di Wang, Xiangyu Guo, Chaowen Guan, Shi Li, Jinhui Xu:
Estimating Stochastic Linear Combination of Non-Linear Regressions. AAAI 2020: 6137-6144 - [c17]Mengdi Huai, Chenglin Miao, Jinduo Liu, Di Wang, Jingyuan Chou, Aidong Zhang:
Global Interpretation for Patient Similarity Learning. BIBM 2020: 589-594 - [c16]Di Wang, Hanshen Xiao, Srinivas Devadas, Jinhui Xu:
On Differentially Private Stochastic Convex Optimization with Heavy-tailed Data. ICML 2020: 10081-10091 - [c15]Di Wang, Jinhui Xu:
Escaping Saddle Points of Empirical Risk Privately and Scalably via DP-Trust Region Method. ECML/PKDD (3) 2020: 90-106 - [i13]Tianhang Zheng, Di Wang, Baochun Li, Jinhui Xu:
Towards Assessment of Randomized Mechanisms for Certifying Adversarial Robustness. CoRR abs/2005.07347 (2020) - [i12]Di Wang, Xiangyu Guo, Chaowen Guan, Shi Li, Jinhui Xu:
Estimating Stochastic Linear Combination of Non-linear Regressions Efficiently and Scalably. CoRR abs/2010.09265 (2020) - [i11]Di Wang, Xiangyu Guo, Shi Li, Jinhui Xu:
Robust High Dimensional Expectation Maximization Algorithm via Trimmed Hard Thresholding. CoRR abs/2010.09576 (2020) - [i10]Di Wang, Hanshen Xiao, Srini Devadas, Jinhui Xu:
On Differentially Private Stochastic Convex Optimization with Heavy-tailed Data. CoRR abs/2010.11082 (2020) - [i9]Di Wang, Jiahao Ding, Zejun Xie, Miao Pan, Jinhui Xu:
Differentially Private (Gradient) Expectation Maximization Algorithm with Statistical Guarantees. CoRR abs/2010.13520 (2020) - [i8]Di Wang, Marco Gaboardi, Adam D. Smith, Jinhui Xu:
Empirical Risk Minimization in the Non-interactive Local Model of Differential Privacy. CoRR abs/2011.05934 (2020)
2010 – 2019
- 2019
- [j1]Di Wang, Jinhui Xu:
Faster constrained linear regression via two-step preconditioning. Neurocomputing 364: 280-296 (2019) - [c14]Di Wang, Jinhui Xu:
Differentially Private Empirical Risk Minimization with Smooth Non-Convex Loss Functions: A Non-Stationary View. AAAI 2019: 1182-1189 - [c13]Di Wang, Adam D. Smith, Jinhui Xu:
Noninteractive Locally Private Learning of Linear Models via Polynomial Approximations. ALT 2019: 897-902 - [c12]Di Wang, Jinhui Xu, Yang He:
Estimating Sparse Covariance Matrix Under Differential Privacy via Thresholding. CISS 2019: 1-5 - [c11]Hongjiang Lei, Di Wang, Ki-Hong Park, Imran Shafique Ansari, Gaofeng Pan, Mohamed-Slim Alouini:
On Secure UAV Communication Systems with Randomly Located Eavesdroppers. ICCC 2019: 201-206 - [c10]Di Wang, Changyou Chen, Jinhui Xu:
Differentially Private Empirical Risk Minimization with Non-convex Loss Functions. ICML 2019: 6526-6535 - [c9]Di Wang, Jinhui Xu:
On Sparse Linear Regression in the Local Differential Privacy Model. ICML 2019: 6628-6637 - [c8]Mengdi Huai, Di Wang, Chenglin Miao, Jinhui Xu, Aidong Zhang:
Privacy-aware Synthesizing for Crowdsourced Data. IJCAI 2019: 2542-2548 - [c7]Di Wang, Jinhui Xu:
Lower Bound of Locally Differentially Private Sparse Covariance Matrix Estimation. IJCAI 2019: 4788-4794 - [c6]Di Wang, Jinhui Xu:
Principal Component Analysis in the Local Differential Privacy Model. IJCAI 2019: 4795-4801 - [c5]Yunus Esencayi, Marco Gaboardi, Shi Li, Di Wang:
Facility Location Problem in Differential Privacy Model Revisited. NeurIPS 2019: 8489-8498 - [i7]Di Wang, Jinhui Xu:
Differentially Private High Dimensional Sparse Covariance Matrix Estimation. CoRR abs/1901.06413 (2019) - [i6]Di Wang, Huanyu Zhang, Marco Gaboardi, Jinhui Xu:
Estimating Smooth GLM in Non-interactive Local Differential Privacy Model with Public Unlabeled Data. CoRR abs/1910.00482 (2019) - [i5]Yunus Esencayi, Marco Gaboardi, Shi Li, Di Wang:
Facility Location Problem in Differential Privacy Model Revisited. CoRR abs/1910.12050 (2019) - 2018
- [c4]Di Wang, Jinhui Xu:
Large Scale Constrained Linear Regression Revisited: Faster Algorithms via Preconditioning. AAAI 2018: 1439-1446 - [c3]Di Wang, Mengdi Huai, Jinhui Xu:
Differentially Private Sparse Inverse Covariance Estimation. GlobalSIP 2018: 1139-1143 - [c2]Di Wang, Marco Gaboardi, Jinhui Xu:
Empirical Risk Minimization in Non-interactive Local Differential Privacy Revisited. NeurIPS 2018: 973-982 - [i4]Di Wang, Jinhui Xu:
Large Scale Constrained Linear Regression Revisited: Faster Algorithms via Preconditioning. CoRR abs/1802.03337 (2018) - [i3]Di Wang, Marco Gaboardi, Jinhui Xu:
Efficient Empirical Risk Minimization with Smooth Loss Functions in Non-interactive Local Differential Privacy. CoRR abs/1802.04085 (2018) - [i2]Di Wang, Minwei Ye, Jinhui Xu:
Differentially Private Empirical Risk Minimization Revisited: Faster and More General. CoRR abs/1802.05251 (2018) - [i1]Di Wang, Adam D. Smith, Jinhui Xu:
Differentially Private Empirical Risk Minimization in Non-interactive Local Model via Polynomial of Inner Product Approximation. CoRR abs/1812.06825 (2018) - 2017
- [c1]Di Wang, Minwei Ye, Jinhui Xu:
Differentially Private Empirical Risk Minimization Revisited: Faster and More General. NIPS 2017: 2722-2731
Coauthor Index
[j30] [j28] [c78] [c77] [c76] [c75] [c74] [c72] [c71] [c69] [c68] [i135] [i132] [i131] [i130] [i128] [i126] [i122] [i119] [i117] [i116] [i115] [i114] [i111] [i110] [i109] [i108] [i100] [i96] [i93] [i87] [i85] [i84] [j22] [j16] [c60] [c57] [c56] [c54] [c49] [c47] [i77] [i76] [i72] [i71] [i70] [i67] [i66] [i64] [i63] [i61] [i56] [i55] [i54] [i53] [i52] [i51] [i49] [i48] [j13] [c43] [c42] [c41] [c38] [i45] [i25] [i24] [c27] [c24] [i18] [i15]
[j34] [j27] [c79] [c66] [i129] [i127] [i124] [i97] [i81] [j23] [j19] [j17] [j14] [c52] [c51] [c48] [c45] [i65] [i50] [j13] [c41] [i31] [c30] [c25] [i23] [i20] [j10] [j9] [j8] [c22] [j7] [j5] [j4] [j3] [j2] [c20] [c18] [c16] [c15] [i13] [i12] [i11] [i10] [i9] [i8] [j1] [c14] [c13] [c12] [c10] [c9] [c8] [c7] [c6] [i7] [i6] [c4] [c3] [c2] [i4] [i3] [i2] [i1] [c1]
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