Zhou, Dengyong

30 publications

AAAI 2021 Post-Training Quantization with Multiple Points: Mixed Precision Without Mixed Precision Xingchao Liu, Mao Ye, Dengyong Zhou, Qiang Liu

ICLR 2020 Doubly Robust Bias Reduction in Infinite Horizon Off-Policy Estimation Ziyang Tang, Yihao Feng, Lihong Li, Dengyong Zhou, Qiang Liu

ICLR 2018 Action-Dependent Control Variates for Policy Optimization via Stein Identity Hao Liu, Yihao Feng, Yi Mao, Dengyong Zhou, Jian Peng, Qiang Liu

NeurIPS 2018 Breaking the Curse of Horizon: Infinite-Horizon Off-Policy Estimation Qiang Liu, Lihong Li, Ziyang Tang, Dengyong Zhou

ICLR 2018 On the Discrimination-Generalization Tradeoff in GANs Pengchuan Zhang, Qiang Liu, Dengyong Zhou, Tao Xu, Xiaodong He

ICLR 2018 Towards Neural Phrase-Based Machine Translation Po-Sen Huang, Chong Wang, Sitao Huang, Dengyong Zhou, Li Deng

ICLR 2017 Neuro-Symbolic Program Synthesis Emilio Parisotto, Abdel-rahman Mohamed, Rishabh Singh, Lihong Li, Dengyong Zhou, Pushmeet Kohli

ICML 2017 Provably Optimal Algorithms for Generalized Linear Contextual Bandits Lihong Li, Yu Lu, Dengyong Zhou

ICML 2017 Sequence Modeling via Segmentations Chong Wang, Yining Wang, Po-Sen Huang, Abdelrahman Mohamed, Dengyong Zhou, Li Deng

ICML 2017 Stochastic Variance Reduction Methods for Policy Evaluation Simon S. Du, Jianshu Chen, Lihong Li, Lin Xiao, Dengyong Zhou

JMLR 2016 Double or Nothing: Multiplicative Incentive Mechanisms for Crowdsourcing Nihar B. Shah, Dengyong Zhou

ICML 2016 Exact Exponent in Optimal Rates for Crowdsourcing Chao Gao, Yu Lu, Dengyong Zhou

ICML 2016 No Oops, You Won’t Do It Again: Mechanisms for Self-Correction in Crowdsourcing Nihar Shah, Dengyong Zhou

JMLR 2016 Spectral Methods Meet EM: A Provably Optimal Algorithm for Crowdsourcing Yuchen Zhang, Xi Chen, Dengyong Zhou, Michael I. Jordan

ICML 2015 Approval Voting and Incentives in Crowdsourcing Nihar Shah, Dengyong Zhou, Yuval Peres

NeurIPS 2015 Double or Nothing: Multiplicative Incentive Mechanisms for Crowdsourcing Nihar Bhadresh Shah, Dengyong Zhou

AAAI 2015 On the Impossibility of Convex Inference in Human Computation Nihar B. Shah, Dengyong Zhou

JMLR 2015 Statistical Decision Making for Optimal Budget Allocation in Crowd Labeling Xi Chen, Qihang Lin, Dengyong Zhou

ICML 2014 Aggregating Ordinal Labels from Crowds by Minimax Conditional Entropy Dengyong Zhou, Qiang Liu, John Platt, Christopher Meek

NeurIPS 2014 Spectral Methods Meet EM: A Provably Optimal Algorithm for Crowdsourcing Yuchen Zhang, Xi Chen, Dengyong Zhou, Michael I Jordan

ICML 2013 Optimistic Knowledge Gradient Policy for Optimal Budget Allocation in Crowdsourcing Xi Chen, Qihang Lin, Dengyong Zhou

NeurIPS 2012 Learning from the Wisdom of Crowds by Minimax Entropy Dengyong Zhou, Sumit Basu, Yi Mao, John C. Platt

ICML 2011 Hierarchical Classification via Orthogonal Transfer Lin Xiao, Dengyong Zhou, Mingrui Wu

ICML 2007 Spectral Clustering and Transductive Learning with Multiple Views Dengyong Zhou, Christopher J. C. Burges

NeurIPS 2006 Learning with Hypergraphs: Clustering, Classification, and Embedding Dengyong Zhou, Jiayuan Huang, Bernhard Schölkopf

ICML 2005 Learning from Labeled and Unlabeled Data on a Directed Graph Dengyong Zhou, Jiayuan Huang, Bernhard Schölkopf

NeurIPS 2004 Semi-Supervised Learning on Directed Graphs Dengyong Zhou, Thomas Hofmann, Bernhard Schölkopf

NeurIPS 2003 Learning with Local and Global Consistency Dengyong Zhou, Olivier Bousquet, Thomas N. Lal, Jason Weston, Bernhard Schölkopf

NeurIPS 2003 Ranking on Data Manifolds Dengyong Zhou, Jason Weston, Arthur Gretton, Olivier Bousquet, Bernhard Schölkopf

NeurIPS 2003 Semi-Supervised Protein Classification Using Cluster Kernels Jason Weston, Dengyong Zhou, André Elisseeff, William S. Noble, Christina S. Leslie