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ORCIDWei Cao 0007
Person information
- affiliation: Microsoft Research Asia, Machine Learning Group, Beijing, China
- affiliation (PhD 2018): Tsinghua University, Institute of Interdisciplinary Information Sciences, Beijing, China
Other persons with the same name
- Wei Cao — disambiguation page
- Wei Cao 0001 — National University of Singapore, Department of Electrical and Computer Engineering, Singapore
- Wei Cao 0002
![[0000-0003-0339-7093]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0003-0339-7093")
— Fudan University, State Key Laboratory of ASIC and System, Shanghai, China - Wei Cao 0003 — University of Electronic Science and Technology of China, National Key Laboratory of Communications, Chengdu, China
- Wei Cao 0004 — Minnan Normal University, School of Mathematics and Statistics, Zhangzhou, China (and 3 more)
- Wei Cao 0005 — Sun Yat-Sen University, Planetary Environmental and Astrobiological Laboratory, School of Atmospheric Sciences, Zhuhai, China (and 2 more)
- Wei Cao 0006 — Alibaba Group, Alibaba Cloud Computing Ltd, Hangzhou, China (and 1 more)
- Wei Cao 0008 — China University of Petroleum, College of Computer Science and Technology, Qingdao, China (and 1 more)
- Wei Cao 0009 — University of Southampton, Optoelectronics Research Centre, Southampton, UK
- Wei Cao 0010 — Chinese Academy of Sciences, Institute of Computing Technology, State Key Laboratory of Computer Architecture, Beijing, China
- Wei Cao 0011 — Qiqihar University, College of Computer and Control Engineering, Qiqihar, China (and 1 more)
- Wei Cao 0012 — Hefei University of Technology, School of Economics, Hefei, China (and 1 more)
- Wei Cao 0014 — Tsinghua University, Department of Automation, Beijing National Research Center for Information Science and Technology (BNRIST), Beijing, China (and 1 more)
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2020 – today
- 2024
[j3]Velma K. Lopez, Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O'Dea, Madeline Adee, Turgay Ayer, Jagpreet Chhatwal, Ozden O. Dalgic, Mary A. Ladd, Benjamin P. Linas, Peter P. Mueller, Jade Xiao, Johannes Bracher, Alvaro J. Castro Rivadeneira, Aaron Gerding, Tilmann Gneiting, Yuxin Huang, Dasuni Jayawardena, Abdul H. Kanji, Khoa Le, Anja Mühlemann, Jarad Niemi, Evan L. Ray, Ariane Stark, Yijin Wang, Nutcha Wattanachit, Martha W. Zorn, Sen Pei, Jeffrey Shaman, Teresa K. Yamana, Samuel R. Tarasewicz, Daniel J. Wilson, Sid Baccam, Heidi Gurung, Steve Stage, Brad Suchoski, Lei Gao, Zhiling Gu, Myungjin Kim, Xinyi Li, Guannan Wang, Lily Wang, Yueying Wang, Shan Yu, Lauren Gardner, Sonia Jindal, Maximilian Marshall, Kristen Nixon, Juan Dent, Alison L. Hill, Joshua Kaminsky, Elizabeth C. Lee, Joseph Chadi Lemaitre, Justin Lessler, Claire P. Smith, Shaun Truelove, Matt Kinsey, Luke C. Mullany, Kaitlin Rainwater-Lovett, Lauren Shin, Katharine Tallaksen, Shelby Wilson, Dean Karlen, Lauren A. Castro, Geoffrey Fairchild, Isaac Michaud, Dave Osthus, Jiang Bian, Wei Cao, Zhifeng Gao, Juan Lavista Ferres, Chaozhuo Li, Tie-Yan Liu, Xing Xie, Shun Zhang, Shun Zheng, Matteo Chinazzi, Jessica T. Davis, Kunpeng Mu, Ana L. Pastore y Piontti, Alessandro Vespignani, Xinyue Xiong, Robert Walraven, Jinghui Chen, Quanquan Gu, Lingxiao Wang, Pan Xu, Weitong Zhang, Difan Zou, Graham Casey Gibson, Daniel Sheldon, Ajitesh Srivastava, Aniruddha Adiga, Benjamin Hurt, Gursharn Kaur, Bryan Lewis, Madhav V. Marathe, Akhil Sai Peddireddy, Przemyslaw J. Porebski, Srinivasan Venkatramanan, Lijing Wang, Pragati V. Prasad, Jo W. Walker, Alexander E. Webber, Rachel B. Slayton, Matthew Biggerstaff, Nicholas G. Reich, Michael A. Johansson:
Challenges of COVID-19 Case Forecasting in the US, 2020-2021. PLoS Comput. Biol. 20(5): 1011200 (2024)- [j2]Chenguo Lin, Xumeng Wen, Wei Cao, Congrui Huang, Jiang Bian, Stephen Lin, Zhirong Wu:
NuTime: Numerically Multi-Scaled Embedding for Large- Scale Time-Series Pretraining. Trans. Mach. Learn. Res. 2024 (2024) - 2023
- [c19]Hangting Ye, Zhining Liu, Xinyi Shen, Wei Cao, Shun Zheng, Xiaofan Gui, Huishuai Zhang, Yi Chang, Jiang Bian:
UADB: Unsupervised Anomaly Detection Booster. ICDE 2023: 2593-2606 - [c18]Hangting Ye, Zhining Liu, Wei Cao, Amir M. Amiri, Jiang Bian, Yi Chang, Jon D. Lurie, Jim Weinstein, Tie-Yan Liu:
Web-based Long-term Spine Treatment Outcome Forecasting. KDD 2023: 3082-3092 - [c17]Jiawen Zhang, Shun Zheng, Wei Cao, Jiang Bian, Jia Li:
Warpformer: A Multi-scale Modeling Approach for Irregular Clinical Time Series. KDD 2023: 3273-3285 - [i13]Hangting Ye, Zhining Liu, Xinyi Shen, Wei Cao, Shun Zheng, Xiaofan Gui, Huishuai Zhang, Yi Chang, Jiang Bian:
UADB: Unsupervised Anomaly Detection Booster. CoRR abs/2306.01997 (2023) - [i12]Jiawen Zhang, Shun Zheng, Wei Cao, Jiang Bian, Jia Li:
Warpformer: A Multi-scale Modeling Approach for Irregular Clinical Time Series. CoRR abs/2306.09368 (2023) - [i11]Chenguo Lin, Xumeng Wen, Wei Cao, Congrui Huang, Jiang Bian, Stephen Lin, Zhirong Wu:
NuTime: Numerically Multi-Scaled Embedding for Large-Scale Time Series Pretraining. CoRR abs/2310.07402 (2023) - 2022
- [c16]Yuting Xing, Hangting Ye, Xiaoyu Zhang, Wei Cao, Shun Zheng, Jiang Bian, Yike Guo:
A continuous glucose monitoring measurements forecasting approach via sporadic blood glucose monitoring. BIBM 2022: 860-863 - [c15]Swati Sharma, Srinivasan Iyengar, Shun Zheng, Kshitij Kapoor, Wei Cao, Jiang Bian, Shivkumar Kalyanaraman, John Lemmon:
A Graph-based Spatiotemporal Model for Energy Markets. CIKM 2022: 4459-4463 - [c14]Wei Fan, Shun Zheng, Xiaohan Yi, Wei Cao, Yanjie Fu, Jiang Bian, Tie-Yan Liu:
DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting. ICLR 2022 - [c13]Xiaozhuang Song, Shun Zheng, Wei Cao, James J. Q. Yu, Jiang Bian:
Efficient and Effective Multi-task Grouping via Meta Learning on Task Combinations. NeurIPS 2022 - [i10]Wei Fan, Shun Zheng, Xiaohan Yi, Wei Cao, Yanjie Fu, Jiang Bian, Tie-Yan Liu:
DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting. CoRR abs/2203.07681 (2022) - [i9]Tianping Zhang, Yizhuo Zhang, Wei Cao, Jiang Bian, Xiaohan Yi, Shun Zheng, Jian Li:
Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures. CoRR abs/2207.01186 (2022) - [i8]Tianping Zhang, Zheyu Zhang, Zhiyuan Fan, Haoyan Luo, Fengyuan Liu, Wei Cao, Jian Li:
OpenFE: Automated Feature Generation beyond Expert-level Performance. CoRR abs/2211.12507 (2022) - 2021
- [c12]Shun Zheng, Wei Cao, Wei Xu, Jiang Bian:
Revisiting the Evaluation of End-to-end Event Extraction. ACL/IJCNLP (Findings) 2021: 4609-4617 - [c11]Shun Zheng, Zhifeng Gao, Wei Cao, Jiang Bian, Tie-Yan Liu:
HierST: A Unified Hierarchical Spatial-temporal Framework for COVID-19 Trend Forecasting. CIKM 2021: 4383-4392 - [i7]Zhining Liu, Zhepei Wei, Erxin Yu, Qiang Huang, Kai Guo, Boyang Yu, Zhaonian Cai, Hangting Ye, Wei Cao, Jiang Bian, Pengfei Wei, Jing Jiang, Yi Chang:
IMBENS: Ensemble Class-imbalanced Learning in Python. CoRR abs/2111.12776 (2021) - [i6]Zhining Liu, Pengfei Wei, Zhepei Wei, Boyang Yu, Jing Jiang, Wei Cao, Jiang Bian, Yi Chang:
Towards Inter-class and Intra-class Imbalance in Class-imbalanced Learning. CoRR abs/2111.12791 (2021) - 2020
- [c10]Zhining Liu, Wei Cao, Zhifeng Gao, Jiang Bian, Hechang Chen, Yi Chang, Tie-Yan Liu:
Self-paced Ensemble for Highly Imbalanced Massive Data Classification. ICDE 2020: 841-852 - [c9]Zhining Liu, Pengfei Wei, Jing Jiang, Wei Cao, Jiang Bian, Yi Chang:
MESA: Boost Ensemble Imbalanced Learning with MEta-SAmpler. NeurIPS 2020 - [i5]Zhining Liu, Pengfei Wei, Jing Jiang, Wei Cao, Jiang Bian, Yi Chang:
MESA: Boost Ensemble Imbalanced Learning with MEta-SAmpler. CoRR abs/2010.08830 (2020)
2010 – 2019
- 2019
- [c8]Shun Zheng, Wei Cao, Wei Xu, Jiang Bian:
Doc2EDAG: An End-to-End Document-level Framework for Chinese Financial Event Extraction. EMNLP/IJCNLP (1) 2019: 337-346 - [i4]Shun Zheng, Wei Cao, Wei Xu, Jiang Bian:
Doc2EDAG: An End-to-End Document-level Framework for Chinese Financial Event Extraction. CoRR abs/1904.07535 (2019) - [i3]Dong Wang, Yitong Li, Wei Cao, Liqun Chen, Qi Wei, Lawrence Carin:
LMVP: Video Predictor with Leaked Motion Information. CoRR abs/1906.10101 (2019) - [i2]Zhining Liu, Wei Cao, Zhifeng Gao, Jiang Bian, Hechang Chen, Yi Chang, Tie-Yan Liu:
Self-paced Ensemble for Highly Imbalanced Massive Data Classification. CoRR abs/1909.03500 (2019) - 2018
- [c7]Dong Wang, Junbo Zhang, Wei Cao, Jian Li, Yu Zheng:
When Will You Arrive? Estimating Travel Time Based on Deep Neural Networks. AAAI 2018: 2500-2507 - [c6]Wei Cao, Dong Wang, Jian Li, Hao Zhou, Lei Li, Yitan Li:
BRITS: Bidirectional Recurrent Imputation for Time Series. NeurIPS 2018: 6776-6786 - [i1]Wei Cao, Dong Wang, Jian Li, Hao Zhou, Lei Li, Yitan Li:
BRITS: Bidirectional Recurrent Imputation for Time Series. CoRR abs/1805.10572 (2018) - 2017
- [c5]Dong Wang, Wei Cao, Jian Li, Jieping Ye:
DeepSD: Supply-Demand Prediction for Online Car-Hailing Services Using Deep Neural Networks. ICDE 2017: 243-254 - [c4]Wei Cao, Jian Li, Haitao Wang, Kangning Wang, Ruosong Wang, Raymond Chi-Wing Wong, Wei Zhan:
k-Regret Minimizing Set: Efficient Algorithms and Hardness. ICDT 2017: 11:1-11:19 - 2016
- [c3]Dong Wang, Wei Cao, Mengwen Xu, Jian Li:
ETCPS: An Effective and Scalable Traffic Condition Prediction System. DASFAA (2) 2016: 419-436 - [c2]Wei Cao, Zhengwei Wu, Dong Wang, Jian Li, Haishan Wu:
Automatic user identification method across heterogeneous mobility data sources. ICDE 2016: 978-989 - 2015
- [j1]Wei Cao, Jian Li, Shimin Li, Haitao Wang:
Balanced splitting on weighted intervals. Oper. Res. Lett. 43(4): 396-400 (2015) - [c1]Wei Cao, Jian Li, Yufei Tao, Zhize Li:
On Top-k Selection in Multi-Armed Bandits and Hidden Bipartite Graphs. NIPS 2015: 1036-1044
Coauthor Index
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