Dengyong Zhou

Publication Activity (10 Years)

Years Active: 2001-2021
Publications (10 Years): 32

Top Topics

Machine Translation

Query Suggestion

Bayes Error Rate

Top Venues

J. Mach. Learn. Res.

Publications

Xingchao Liu, Mao Ye, Dengyong Zhou, Qiang Liu
Post-training Quantization with Multiple Points: Mixed Precision without Mixed Precision. AAAI (2021)
Xingchao Liu, Mao Ye, Dengyong Zhou, Qiang Liu
Post-training Quantization with Multiple Points: Mixed Precision without Mixed Precision. CoRR (2020)
Nihar B. Shah, Dengyong Zhou
Approval Voting and Incentives in Crowdsourcing. ACM Trans. Economics and Comput. 8 (3) (2020)
Ziyang Tang, Yihao Feng, Lihong Li, Dengyong Zhou, Qiang Liu
Doubly Robust Bias Reduction in Infinite Horizon Off-Policy Estimation. ICLR (2020)
Ziyang Tang, Yihao Feng, Lihong Li, Dengyong Zhou, Qiang Liu
Doubly Robust Bias Reduction in Infinite Horizon Off-Policy Estimation. CoRR (2019)
Po-Sen Huang, Chong Wang, Sitao Huang, Dengyong Zhou, Li Deng
Towards Neural Phrase-based Machine Translation. ICLR (Poster) (2018)
Jiangtao Feng, Lingpeng Kong, Po-Sen Huang, Chong Wang, Da Huang, Jiayuan Mao, Kan Qiao, Dengyong Zhou
Neural Phrase-to-Phrase Machine Translation. CoRR (2018)
Hao Liu, Yihao Feng, Yi Mao, Dengyong Zhou, Jian Peng, Qiang Liu
Action-dependent Control Variates for Policy Optimization via Stein Identity. ICLR (Poster) (2018)
Qiang Liu, Lihong Li, Ziyang Tang, Dengyong Zhou
Breaking the Curse of Horizon: Infinite-Horizon Off-Policy Estimation. CoRR (2018)
Qiang Liu, Lihong Li, Ziyang Tang, Dengyong Zhou
Breaking the Curse of Horizon: Infinite-Horizon Off-Policy Estimation. NeurIPS (2018)
Pengchuan Zhang, Qiang Liu, Dengyong Zhou, Tao Xu, Xiaodong He
On the Discrimination-Generalization Tradeoff in GANs. ICLR (Poster) (2018)
Shayok Chakraborty, Jack W. Stokes, Lin Xiao, Dengyong Zhou, Mady Marinescu, Anil Thomas
Hierarchical learning for automated malware classification. MILCOM (2017)
Simon S. Du, Jianshu Chen, Lihong Li, Lin Xiao, Dengyong Zhou
Stochastic Variance Reduction Methods for Policy Evaluation. CoRR (2017)
Lihong Li, Yu Lu, Dengyong Zhou
Provable Optimal Algorithms for Generalized Linear Contextual Bandits. CoRR (2017)
Po-Sen Huang, Chong Wang, Dengyong Zhou, Li Deng
Neural Phrase-based Machine Translation. CoRR (2017)
Simon S. Du, Jianshu Chen, Lihong Li, Lin Xiao, Dengyong Zhou
Stochastic Variance Reduction Methods for Policy Evaluation. ICML (2017)
Hao Liu, Yihao Feng, Yi Mao, Dengyong Zhou, Jian Peng, Qiang Liu
Sample-efficient Policy Optimization with Stein Control Variate. CoRR (2017)
Emilio Parisotto, Abdel-rahman Mohamed, Rishabh Singh, Lihong Li, Dengyong Zhou, Pushmeet Kohli
Neuro-Symbolic Program Synthesis. ICLR (Poster) (2017)
Pengchuan Zhang, Qiang Liu, Dengyong Zhou, Tao Xu, Xiaodong He
On the Discrimination-Generalization Tradeoff in GANs. CoRR (2017)
Lihong Li, Yu Lu, Dengyong Zhou
Provably Optimal Algorithms for Generalized Linear Contextual Bandits. ICML (2017)
Chong Wang, Yining Wang, Po-Sen Huang, Abdelrahman Mohamed, Dengyong Zhou, Li Deng
Sequence Modeling via Segmentations. ICML (2017)
Chong Wang, Yining Wang, Po-Sen Huang, Abdelrahman Mohamed, Dengyong Zhou, Li Deng
Sequence Modeling via Segmentations. CoRR (2017)
Nihar B. Shah, Dengyong Zhou
No Oops, You Won't Do It Again: Mechanisms for Self-correction in Crowdsourcing. ICML (2016)
Nihar B. Shah, Dengyong Zhou
Double or Nothing: Multiplicative Incentive Mechanisms for Crowdsourcing. J. Mach. Learn. Res. 17 (2016)
Chao Gao, Yu Lu, Dengyong Zhou
Exact Exponent in Optimal Rates for Crowdsourcing. ICML (2016)
Yuchen Zhang, Xi Chen, Dengyong Zhou, Michael I. Jordan
Spectral Methods Meet EM: A Provably Optimal Algorithm for Crowdsourcing. J. Mach. Learn. Res. 17 (2016)
Emilio Parisotto, Abdel-rahman Mohamed, Rishabh Singh, Lihong Li, Dengyong Zhou, Pushmeet Kohli
Neuro-Symbolic Program Synthesis. CoRR (2016)
Nihar B. Shah, Dengyong Zhou, Yuval Peres
Approval Voting and Incentives in Crowdsourcing. CoRR (2015)
Xi Chen, Qihang Lin, Dengyong Zhou
Statistical decision making for optimal budget allocation in crowd labeling. J. Mach. Learn. Res. 16 (2015)
Nihar B. Shah, Dengyong Zhou, Yuval Peres
Approval Voting and Incentives in Crowdsourcing. ICML (2015)
Nihar B. Shah, Dengyong Zhou
On the Impossibility of Convex Inference in Human Computation. AAAI (2015)
Dengyong Zhou, Qiang Liu, John C. Platt, Christopher Meek, Nihar B. Shah
Regularized Minimax Conditional Entropy for Crowdsourcing. CoRR (2015)
Nihar B. Shah, Dengyong Zhou
On the Impossibility of Convex Inference in Human Computation. CoRR (2014)
Xi Chen, Qihang Lin, Dengyong Zhou
Statistical Decision Making for Optimal Budget Allocation in Crowd Labeling. CoRR (2014)
Yuchen Zhang, Xi Chen, Dengyong Zhou, Michael I. Jordan
Spectral Methods meet EM: A Provably Optimal Algorithm for Crowdsourcing. NIPS (2014)
Dengyong Zhou, Qiang Liu, John C. Platt, Christopher Meek
Aggregating Ordinal Labels from Crowds by Minimax Conditional Entropy. ICML (2014)
Nihar B. Shah, Dengyong Zhou
Double or Nothing: Multiplicative Incentive Mechanisms for Crowdsourcing. CoRR (2014)
Xi Chen, Qihang Lin, Dengyong Zhou
Optimistic Knowledge Gradient Policy for Optimal Budget Allocation in Crowdsourcing. ICML (3) (2013)
Hongwei Li, Bin Yu, Dengyong Zhou
Error Rate Bounds in Crowdsourcing Models. CoRR (2013)
Dengyong Zhou, John C. Platt, Sumit Basu, Yi Mao
Learning from the Wisdom of Crowds by Minimax Entropy. NIPS (2012)
Yang Song, Dengyong Zhou, Li-wei He
Query suggestion by constructing term-transition graphs. WSDM (2012)
Hao Ma, Dengyong Zhou, Chao Liu, Michael R. Lyu, Irwin King
Recommender systems with social regularization. WSDM (2011)
Lin Xiao, Dengyong Zhou, Mingrui Wu
Hierarchical Classification via Orthogonal Transfer. ICML (2011)
Yang Song, Dengyong Zhou, Li-wei He
Post-ranking query suggestion by diversifying search results. SIGIR (2011)
Dou Shen, Ying Li, Xiao Li, Dengyong Zhou
Product query classification. CIKM (2009)
Yun Chi, Xiaodan Song, Dengyong Zhou, Koji Hino, Belle L. Tseng
On evolutionary spectral clustering. ACM Trans. Knowl. Discov. Data 3 (4) (2009)
Qiaozhu Mei, Dengyong Zhou, Kenneth Ward Church
Query suggestion using hitting time. CIKM (2008)
Dengyong Zhou, Christopher J. C. Burges
Spectral clustering and transductive learning with multiple views. ICML (2007)
Dengyong Zhou, Chris Burges, Tao Tao
Transductive Link Spam Detection. AIRWeb (2007)
Yun Chi, Xiaodan Song, Dengyong Zhou, Koji Hino, Belle L. Tseng
Evolutionary spectral clustering by incorporating temporal smoothness. KDD (2007)
Gustavo Camps-Valls, Tatyana V. Bandos Marsheva, Dengyong Zhou
Semi-Supervised Graph-Based Hyperspectral Image Classification. IEEE Trans. Geosci. Remote. Sens. 45 (10) (2007)
Jiayuan Huang, Tingshao Zhu, Russell Greiner, Dengyong Zhou, Dale Schuurmans
Information Marginalization on Subgraphs. PKDD (2006)
Dengyong Zhou, Jiayuan Huang, Bernhard Schölkopf
Learning with Hypergraphs: Clustering, Classification, and Embedding. NIPS (2006)
Dengyong Zhou, Bernhard Schölkopf
Regularization on Discrete Spaces. DAGM-Symposium (2005)
Dengyong Zhou, Jiayuan Huang, Bernhard Schölkopf
Learning from labeled and unlabeled data on a directed graph. ICML (2005)
Jason Weston, Christina S. Leslie, Eugene Ie, Dengyong Zhou, André Elisseeff, William Stafford Noble
Semi-supervised protein classification using cluster kernels. Bioinform. 21 (15) (2005)
Dengyong Zhou, Bernhard Schölkopf, Thomas Hofmann
Semi-supervised Learning on Directed Graphs. NIPS (2004)
Dengyong Zhou, Bernhard Schölkopf
Learning from Labeled and Unlabeled Data Using Random Walks. DAGM-Symposium (2004)
Jason Weston, Christina S. Leslie, Dengyong Zhou, André Elisseeff, William Stafford Noble
Semi-supervised Protein Classification Using Cluster Kernels. NIPS (2003)
Dengyong Zhou, Jason Weston, Arthur Gretton, Olivier Bousquet, Bernhard Schölkopf
Ranking on Data Manifolds. NIPS (2003)
Dengyong Zhou, Olivier Bousquet, Thomas Navin Lal, Jason Weston, Bernhard Schölkopf
Learning with Local and Global Consistency. NIPS (2003)
Dengyong Zhou, Ruwei Dai
The control structure of artificial creatures. Artif. Life Robotics 5 (3) (2001)