Wei Chen (陈薇) is a researcher in Artificial Intelligence Group, Microsoft Research Asia. Her current research interests include: distributed machine learning, machine learning for games, deep learning theory, mechanism design, and learning to rank. Before she joined Microsoft in July 2011, she obtained her Ph. D. in probability and mathematic statistics from Academy of Mathematics and System Science, Chinese Academy of Sciences.
Wei Chen, Tie-Yan Liu, and Xinxin Yang, Reinforcement Learning Behaviors in Sponsored Search, Applied Stochastic Models in Business and Industry (ASMB),2016.
Shizhao Sun, Wei Chen, Liwei Wang, and Tie-Yan Liu, On the Depth of Deep Neural Networks: A Theoretical View, In Proceedings of the 30th International Association for the Advancement of Artificial Intelligence Conference (AAAI), 2016.
Wei Chen, Tao Qin, Weidong Ma, and Tie-Yan Liu. Advances in Ad Auction Mechanism Design for Sponsored Search. Book chapter in Multi-Agent System and its Applications. Tsinghua University Press, Beijing, 2015. (ISBN 978-7-302-40252-7, in Chinese)
Tie-Yan Liu, Wei Chen, and Tao Qin, Mechanism Learning with Mechanism Induced Data, Senior Member Track, In Proceedings of the 29th International Association for the Advancement of Artificial Intelligence Conference (AAAI), 2015.
Haifang Li, Tian Fei, Wei Chen, Tao Qin, Zhiming Ma, and Tie-Yan Liu, Generalization Analysis for Game-Theoretic Machine Learning, Proceedings of the 29th International Association for the Advancement of Artificial Intelligence Conference (AAAI), 2015.
Tao Qin, Wei Chen, and Tie-Yan Liu, Sponsored Search Auctions: Recent Advances and Future Directions, ACM Transactions on Intelligent Systems and Technology (TIST),5 (4), 2014.
Wei Chen, Di He, Tie-Yan Liu, Tao Qin, Yixin Tao, and Liwei Wang, Generalized Second Price Auction with Probabilistic Broad Match, In Proceedings of the 15th ACM Conference on Economics and Computation (EC), Pages 39-56, 2014.
Fei Tian, Haifang Li, Wei Chen, Tao Qin and Tie-Yan Liu, Agent Behavior Prediction and Its Generalization Analysis, In Proceedings of the 28th International Association for the Advancement of Artificial Intelligence Conference (AAAI), Pages 1300-1306, 2014.
Jun Feng, Jiang Bian, Taifeng Wang, Wei Chen, Xiaoyan Zhu and Tie-Yan Liu, Sampling Dilemma: Towards Effective Data Sampling for Click Prediction in Sponsored Search, In Proceedings of 7th ACM Conference on Web Search and Data Mining (WSDM), Pages 130-112, 2014.
Di He, Wei Chen, Liwei Wang, and Tie-Yan Liu, Online Learning for Auction Mechanism in Bandit Setting, Decision Support Systems (DSS), Vol 56, Pages 379-386, 2013.
Di He, Wei Chen, Liwei Wang, and Tie-Yan Liu, Probabilistic Broad Match for Sponsored Search Auctions, EC AdAuction Workshop 2013.
Yining Wang, Liwei Wang, Yuanzhi Li, Di He, Wei Chen, and Tie-Yan Liu, A Theoretical Analysis of NDCG Type Ranking Measures, In Proceedings of the 26th Annual Conference on Learning Theory (COLT), Pages 25-54,2013
Di He, Wei Chen, Liwei Wang, Tie-Yan Liu, A Game-theoretic Machine Learning Approach for Revenue Maximization in Sponsored Search, In Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI), Pages 206-212, 2013.
Lei Yao, Wei Chen, Tie-Yan Liu. Convergence Analysis for Weighted Joint Strategy Fictitious Play in Generalized Second Price Auction, Proceedings of the 10th Conference on Web and Internet Economics (WINE), Pages 489-495, 2012.
Wei Chen, Tie-Yan Liu, and Zhiming Ma, Two-Layer Generalization Analysis for Ranking Using Rademacher Average, Advances in Neural Information Processing Systems 23 (NIPS), Pages 370-378, 2010.
Wei Chen, Tie-Yan Liu, Yanyan Lan, and Zhiming Ma, Ranking Measures and Loss functions in Learning to Rank, Advances in Neural Information Processing Systems 22 (NIPS), Pages 315-323, 2009.
PC member: AAMAS 2015, AAAI 2015, IJCAI 2015, CIKM 2015, ACML 2015
Mailing Address: Tower 2, No. 5 Danling Street, Haidian District, Beijing, P. R. China, 100080