The control structure of artificial creatures. - Dengyong Zhou; Ruwei Dai (Artif. Life Robotics, 2001)

Semi-supervised Protein Classification Using Cluster Kernels. - Jason Weston; Christina S. Leslie; Dengyong Zhou; André Elisseeff; William Stafford Noble (NIPS, 2003)

Learning with Local and Global Consistency. - Dengyong Zhou; Olivier Bousquet; Thomas Navin Lal; Jason Weston; Bernhard Schölkopf (NIPS, 2003)

Ranking on Data Manifolds. - Dengyong Zhou; Jason Weston; Arthur Gretton; Olivier Bousquet; Bernhard Schölkopf (NIPS, 2003)

Learning from Labeled and Unlabeled Data Using Random Walks. - Dengyong Zhou; Bernhard Schölkopf (DAGM-Symposium, 2004)

Semi-supervised Learning on Directed Graphs. - Dengyong Zhou; Bernhard Schölkopf; Thomas Hofmann 001 (NIPS, 2004)

Regularization on Discrete Spaces. - Dengyong Zhou; Bernhard Schölkopf (DAGM-Symposium, 2005)

Learning from labeled and unlabeled data on a directed graph. - Dengyong Zhou; Jiayuan Huang; Bernhard Schölkopf (ICML, 2005)

Semi-supervised protein classification using cluster kernels. - Jason Weston; Christina S. Leslie; Eugene Ie; Dengyong Zhou; André Elisseeff; William Stafford Noble (Bioinform., 2005)

Discrete Regularization. - Dengyong Zhou; Bernhard Schölkopf (Semi-Supervised Learning, 2006)

Learning with Hypergraphs: Clustering, Classification, and Embedding. - Dengyong Zhou; Jiayuan Huang; Bernhard Schölkopf (NIPS, 2006)

Information Marginalization on Subgraphs. - Jiayuan Huang; Tingshao Zhu; Russell Greiner; Dengyong Zhou; Dale Schuurmans (PKDD, 2006)

Transductive Link Spam Detection. - Dengyong Zhou; Chris Burges; Tao Tao (AIRWeb, 2007)

Spectral clustering and transductive learning with multiple views. - Dengyong Zhou; Christopher J. C. Burges (ICML, 2007)

Evolutionary spectral clustering by incorporating temporal smoothness. - Yun Chi; Xiaodan Song; Dengyong Zhou; Koji Hino; Belle L. Tseng (KDD, 2007)

Semi-Supervised Graph-Based Hyperspectral Image Classification. - Gustavo Camps-Valls; Tatyana V. Bandos Marsheva; Dengyong Zhou (IEEE Trans. Geosci. Remote. Sens., 2007)

Query suggestion using hitting time. - Qiaozhu Mei; Dengyong Zhou; Kenneth Ward Church (CIKM, 2008)

Product query classification. - Dou Shen; Ying Li 040; Xiao Li 006; Dengyong Zhou (CIKM, 2009)

On evolutionary spectral clustering. - Yun Chi; Xiaodan Song; Dengyong Zhou; Koji Hino; Belle L. Tseng (ACM Trans. Knowl. Discov. Data, 2009)

Hierarchical Classification via Orthogonal Transfer. - Lin Xiao; Dengyong Zhou; Mingrui Wu (ICML, 2011)

Post-ranking query suggestion by diversifying search results. - Yang Song 008; Dengyong Zhou; Li-wei He (SIGIR, 2011)

Recommender systems with social regularization. - Hao Ma 001; Dengyong Zhou; Chao Liu 001; Michael R. Lyu; Irwin King (WSDM, 2011)

Learning from the Wisdom of Crowds by Minimax Entropy. - Dengyong Zhou; John C. Platt; Sumit Basu; Yi Mao (NIPS, 2012)

Query suggestion by constructing term-transition graphs. - Yang Song 008; Dengyong Zhou; Li-wei He (WSDM, 2012)

Optimistic Knowledge Gradient Policy for Optimal Budget Allocation in Crowdsourcing. - Xi Chen; Qihang Lin; Dengyong Zhou (ICML (3), 2013)

Error Rate Bounds in Crowdsourcing Models. - Hongwei Li; Bin Yu 001; Dengyong Zhou (CoRR, 2013)

Aggregating Ordinal Labels from Crowds by Minimax Conditional Entropy. - Dengyong Zhou; Qiang Liu 001; John C. Platt; Christopher Meek (ICML, 2014)

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

Approval Voting and Incentives in Crowdsourcing. - Nihar B. Shah; Dengyong Zhou; Yuval Peres (ICML, 2015)

Regularized Minimax Conditional Entropy for Crowdsourcing. - Dengyong Zhou; Qiang Liu 001; John C. Platt; Christopher Meek; Nihar B. Shah (CoRR, 2015)

Statistical decision making for optimal budget allocation in crowd labeling. - Xi Chen; Qihang Lin; Dengyong Zhou (J. Mach. Learn. Res., 2015)

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 B. Shah; Dengyong Zhou (ICML, 2016)

Double or Nothing: Multiplicative Incentive Mechanisms for Crowdsourcing. - Nihar B. Shah; Dengyong Zhou (J. Mach. Learn. Res., 2016)

Spectral Methods Meet EM: A Provably Optimal Algorithm for Crowdsourcing. - Yuchen Zhang 002; Xi Chen; Dengyong Zhou; Michael I. Jordan (J. Mach. Learn. Res., 2016)

Neuro-Symbolic Program Synthesis. - Emilio Parisotto; Abdel-rahman Mohamed; Rishabh Singh; Lihong Li 001; Dengyong Zhou; Pushmeet Kohli (ICLR (Poster), 2017)

Stochastic Variance Reduction Methods for Policy Evaluation. - Simon S. Du; Jianshu Chen; Lihong Li 001; Lin Xiao; Dengyong Zhou (ICML, 2017)

Provably Optimal Algorithms for Generalized Linear Contextual Bandits. - Lihong Li 001; Yu Lu; Dengyong Zhou (ICML, 2017)

Sequence Modeling via Segmentations. - Chong Wang 002; Yining Wang; Po-Sen Huang; Abdelrahman Mohamed; Dengyong Zhou; Li Deng 001 (ICML, 2017)

Hierarchical learning for automated malware classification. - Shayok Chakraborty; Jack W. Stokes; Lin Xiao; Dengyong Zhou; Mady Marinescu; Anil Thomas (MILCOM, 2017)

Neural Phrase-based Machine Translation. - Po-Sen Huang; Chong Wang 002; Dengyong Zhou; Li Deng 001 (CoRR, 2017)

Provable Optimal Algorithms for Generalized Linear Contextual Bandits. - Lihong Li 001; Yu Lu; Dengyong Zhou (CoRR, 2017)

Sample-efficient Policy Optimization with Stein Control Variate. - Hao Liu; Yihao Feng; Yi Mao; Dengyong Zhou; Jian Peng 001; Qiang Liu 001 (CoRR, 2017)

Towards Neural Phrase-based Machine Translation. - Po-Sen Huang; Chong Wang 002; Sitao Huang; Dengyong Zhou; Li Deng 001 (ICLR (Poster), 2018)

Action-dependent Control Variates for Policy Optimization via Stein Identity. - Hao Liu; Yihao Feng; Yi Mao; Dengyong Zhou; Jian Peng 001; Qiang Liu 001 (ICLR (Poster), 2018)

On the Discrimination-Generalization Tradeoff in GANs. - Pengchuan Zhang; Qiang Liu 001; Dengyong Zhou; Tao Xu; Xiaodong He 001 (ICLR (Poster), 2018)

Breaking the Curse of Horizon: Infinite-Horizon Off-Policy Estimation. - Qiang Liu 001; Lihong Li 001; Ziyang Tang; Dengyong Zhou (NeurIPS, 2018)

Neural Phrase-to-Phrase Machine Translation. - Jiangtao Feng; Lingpeng Kong; Po-Sen Huang; Chong Wang; Da Huang; Jiayuan Mao; Kan Qiao; Dengyong Zhou (CoRR, 2018)

Doubly Robust Bias Reduction in Infinite Horizon Off-Policy Estimation. - Ziyang Tang; Yihao Feng; Lihong Li 001; Dengyong Zhou; Qiang Liu 001 (ICLR, 2020)

Approval Voting and Incentives in Crowdsourcing. - Nihar B. Shah; Dengyong Zhou (ACM Trans. Economics and Comput., 2020)

Post-training Quantization with Multiple Points: Mixed Precision without Mixed Precision. - Xingchao Liu; Mao Ye 006; Dengyong Zhou; Qiang Liu 001 (AAAI, 2021)