Zhengyuan Zhou

ORCID

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 125

Top Venues

Publications

Zhengyuan Zhou, Kai Chen, Dianlin Hu, Huazhong Shu, Gouenou Coatrieux, Jean-Louis Coatrieux, Yang Chen
Global texture sensitive convolutional transformer for medical image steganalysis. Multim. Syst. 30 (3) (2024)
José H. Blanchet, Renyuan Xu, Zhengyuan Zhou
Delay-Adaptive Learning in Generalized Linear Contextual Bandits. Math. Oper. Res. 49 (1) (2024)
Jingyuan Wang, Perry Dong, Ying Jin, Ruohan Zhan, Zhengyuan Zhou
Adaptively Learning to Select-Rank in Online Platforms. CoRR (2024)
Shengbo Wang, Nian Si, Jose H. Blanchet, Zhengyuan Zhou
Statistical Learning of Distributionally Robust Stochastic Control in Continuous State Spaces. CoRR (2024)
Zijian Liu, Zhengyuan Zhou
Revisiting the Last-Iterate Convergence of Stochastic Gradient Methods. ICLR (2024)
Kai Chen, Zhengyuan Zhou, Yuchen Li, Xu Ji, Jiasong Wu, Jean-Louis Coatrieux, Yang Chen, Gouenou Coatrieux
RED-Net: Residual and Enhanced Discriminative Network for Image Steganalysis in the Internet of Medical Things and Telemedicine. IEEE J. Biomed. Health Informatics 28 (3) (2024)
Ying Jin, Ramki Gummadi, Zhengyuan Zhou, Jose H. Blanchet
Feasible Q-Learning for Average Reward Reinforcement Learning. AISTATS (2024)
Zijian Liu, Zhengyuan Zhou
On the Last-Iterate Convergence of Shuffling Gradient Methods. CoRR (2024)
Xiaoqin Zhang, Jingjing Zheng, Li Zhao, Zhengyuan Zhou, Zhouchen Lin
Tensor Recovery With Weighted Tensor Average Rank. IEEE Trans. Neural Networks Learn. Syst. 35 (1) (2024)
Yuxiao Wen, Yanjun Han, Zhengyuan Zhou
Stochastic contextual bandits with graph feedback: from independence number to MAS number. CoRR (2024)
Zhimei Ren, Zhengyuan Zhou
Dynamic Batch Learning in High-Dimensional Sparse Linear Contextual Bandits. Manag. Sci. 70 (2) (2024)
Yu Xia, Sriram Narayanamoorthy, Zhengyuan Zhou, Joshua Mabry
Simulation-Based Benchmarking of Reinforcement Learning Agents for Personalized Retail Promotions. CoRR (2024)
Zijian Liu, Zhengyuan Zhou
Stochastic Nonsmooth Convex Optimization with Heavy-Tailed Noises. CoRR (2023)
Zijian Liu, Zhengyuan Zhou
Revisiting the Last-Iterate Convergence of Stochastic Gradient Methods. CoRR (2023)
Nian Si, Fan Zhang, Zhengyuan Zhou, Jose H. Blanchet
Distributionally Robust Batch Contextual Bandits. Manag. Sci. 69 (10) (2023)
Michael I. Jordan, Tianyi Lin, Zhengyuan Zhou
Adaptive, Doubly Optimal No-Regret Learning in Strongly Monotone and Exp-Concave Games with Gradient Feedback. CoRR (2023)
Zijian Liu, Perry Dong, Srikanth Jagabathula, Zhengyuan Zhou
Near-Optimal High-Probability Convergence for Non-Convex Stochastic Optimization with Variance Reduction. CoRR (2023)
Zhipeng Liang, Xiaoteng Ma, Jose H. Blanchet, Jiheng Zhang, Zhengyuan Zhou
Single-Trajectory Distributionally Robust Reinforcement Learning. CoRR (2023)
Shengbo Wang, Nian Si, Jose H. Blanchet, Zhengyuan Zhou
On the Foundation of Distributionally Robust Reinforcement Learning. CoRR (2023)
Shengbo Wang, Nian Si, José H. Blanchet, Zhengyuan Zhou
A Finite Sample Complexity Bound for Distributionally Robust Q-learning. AISTATS (2023)
Zhengyuan Zhou, Susan Athey, Stefan Wager
Offline Multi-Action Policy Learning: Generalization and Optimization. Oper. Res. 71 (1) (2023)
Zijian Liu, Jiawei Zhang, Zhengyuan Zhou
Breaking the Lower Bound with (Little) Structure: Acceleration in Non-Convex Stochastic Optimization with Heavy-Tailed Noise. CoRR (2023)
Shengbo Wang, Nian Si, Jose H. Blanchet, Zhengyuan Zhou
Sample Complexity of Variance-reduced Distributionally Robust Q-learning. CoRR (2023)
Zhaonan Qu, Kaixiang Lin, Zhaojian Li, Jiayu Zhou, Zhengyuan Zhou
A Unified Linear Speedup Analysis of Federated Averaging and Nesterov FedAvg. J. Artif. Intell. Res. 78 (2023)
Shengbo Wang, Nian Si, Jose Blanchet, Zhengyuan Zhou
A Finite Sample Complexity Bound for Distributionally Robust Q-learning. CoRR (2023)
Zijian Liu, Jiawei Zhang, Zhengyuan Zhou
Breaking the Lower Bound with (Little) Structure: Acceleration in Non-Convex Stochastic Optimization with Heavy-Tailed Noise. COLT (2023)
Xiaoqin Zhang, Jingjing Zheng, Di Wang, Guiying Tang, Zhengyuan Zhou, Zhouchen Lin
Structured Sparsity Optimization With Non-Convex Surrogates of $\ell _{2,0}$ℓ2,0-Norm: A Unified Algorithmic Framework. IEEE Trans. Pattern Anal. Mach. Intell. 45 (5) (2023)
Yan Chen, Perry Dong, Qinxun Bai, Maria Dimakopoulou, Wei Xu, Zhengyuan Zhou
Society of Agents: Regret Bounds of Concurrent Thompson Sampling. NeurIPS (2022)
Boxiao Chen, Jiashuo Jiang, Jiawei Zhang, Zhengyuan Zhou
Learning to Order for Inventory Systems with Lost Sales and Uncertain Supplies. CoRR (2022)
Zhaonan Qu, Wenzhi Gao, Oliver Hinder, Yinyu Ye, Zhengyuan Zhou
Optimal Diagonal Preconditioning: Theory and Practice. CoRR (2022)
Nathan Kallus, Xiaojie Mao, Kaiwen Wang, Zhengyuan Zhou
Doubly Robust Distributionally Robust Off-Policy Evaluation and Learning. CoRR (2022)
Yuexiang Zhai, Christina Baek, Zhengyuan Zhou, Jiantao Jiao, Yi Ma
Computational Benefits of Intermediate Rewards for Goal-Reaching Policy Learning. J. Artif. Intell. Res. 73 (2022)
Zhengyuan Zhou, Panayotis Mertikopoulos, Nicholas Bambos, Peter W. Glynn, Yinyu Ye
Distributed Stochastic Optimization with Large Delays. Math. Oper. Res. 47 (3) (2022)
Wei Zhang, Yanjun Han, Zhengyuan Zhou, Aaron Flores, Tsachy Weissman
Leveraging the Hints: Adaptive Bidding in Repeated First-Price Auctions. CoRR (2022)
Xiaoteng Ma, Zhipeng Liang, Jose H. Blanchet, Mingwen Liu, Li Xia, Jiheng Zhang, Qianchuan Zhao, Zhengyuan Zhou
Distributionally Robust Offline Reinforcement Learning with Linear Function Approximation. CoRR (2022)
Ilai Bistritz, Zhengyuan Zhou, Xi Chen, Nicholas Bambos, José H. Blanchet
No Weighted-Regret Learning in Adversarial Bandits with Delays. J. Mach. Learn. Res. 23 (2022)
Nathan Kallus, Xiaojie Mao, Kaiwen Wang, Zhengyuan Zhou
Doubly Robust Distributionally Robust Off-Policy Evaluation and Learning. ICML (2022)
Zhimei Ren, Zhengyuan Zhou, Jayant R. Kalagnanam
Batched Learning in Generalized Linear Contextual Bandits With General Decision Sets. IEEE Control. Syst. Lett. 6 (2022)
Wei Zhang, Yanjun Han, Zhengyuan Zhou, Aaron Flores, Tsachy Weissman
Leveraging the Hints: Adaptive Bidding in Repeated First-Price Auctions. NeurIPS (2022)
Shi Dong, Benjamin Van Roy, Zhengyuan Zhou
Simple Agent, Complex Environment: Efficient Reinforcement Learning with Agent States. J. Mach. Learn. Res. 23 (2022)
Zijian Liu, Qinxun Bai, Jose H. Blanchet, Perry Dong, Wei Xu, Zhengqing Zhou, Zhengyuan Zhou
Distributionally Robust Q-Learning. ICML (2022)
Ilai Bistritz, Andrew Ward, Zhengyuan Zhou, Nicholas Bambos
Smart Greedy Distributed Energy Allocation: A Random Games Approach. IEEE Trans. Autom. Control. 67 (5) (2022)
Ruohan Zhan, Zhimei Ren, Susan Athey, Zhengyuan Zhou
Policy Learning with Adaptively Collected Data. CoRR (2021)
Maria Dimakopoulou, Zhimei Ren, Zhengyuan Zhou
Online Multi-Armed Bandits with Adaptive Inference. NeurIPS (2021)
Wei Zhang, Brendan Kitts, Yanjun Han, Zhengyuan Zhou, Tingyu Mao, Hao He, Shengjun Pan, Aaron Flores, San Gultekin, Tsachy Weissman
MEOW: A Space-Efficient Nonparametric Bid Shading Algorithm. KDD (2021)
Maria Dimakopoulou, Zhimei Ren, Zhengyuan Zhou
Doubly-Adaptive Thompson Sampling for Multi-Armed and Contextual Bandits. CoRR (2021)
Ilai Bistritz, Zhengyuan Zhou, Xi Chen, Nicholas Bambos, Jose H. Blanchet
No Discounted-Regret Learning in Adversarial Bandits with Delays. CoRR (2021)
Zhengyuan Zhou, Panayotis Mertikopoulos, Aris L. Moustakas, Nicholas Bambos, Peter W. Glynn
Robust Power Management via Learning and Game Design. Oper. Res. 69 (1) (2021)
Xiaoqin Zhang, Di Wang, Zhengyuan Zhou, Yi Ma
Robust Low-Rank Tensor Recovery with Rectification and Alignment. IEEE Trans. Pattern Anal. Mach. Intell. 43 (1) (2021)
Zhengyuan Zhou, Panayotis Mertikopoulos, Nicholas Bambos, Peter W. Glynn, Yinyu Ye
Distributed stochastic optimization with large delays. CoRR (2021)
Yuexiang Zhai, Christina Baek, Zhengyuan Zhou, Jiantao Jiao, Yi Ma
Computational Benefits of Intermediate Rewards for Hierarchical Planning. CoRR (2021)
Tianyi Lin, Zhengyuan Zhou, Wenjia Ba, Jiawei Zhang
Optimal No-Regret Learning in Strongly Monotone Games with Bandit Feedback. CoRR (2021)
Jingwei Zhang, Zhuoran Yang, Zhengyuan Zhou, Zhaoran Wang
Provably Sample Efficient Reinforcement Learning in Competitive Linear Quadratic Systems. L4DC (2021)
Shi Dong, Benjamin Van Roy, Zhengyuan Zhou
Simple Agent, Complex Environment: Efficient Reinforcement Learning with Agent State. CoRR (2021)
Chaobing Song, Zhengyuan Zhou, Yichao Zhou, Yong Jiang, Yi Ma
Optimistic Dual Extrapolation for Coherent Non-monotone Variational Inequalities. CoRR (2021)
Zhimei Ren, Zhengyuan Zhou, Jayant R. Kalagnanam
Batched Learning in Generalized Linear Contextual Bandits with General Decision Sets. ACC (2021)
Zhengqing Zhou, Qinxun Bai, Zhengyuan Zhou, Linhai Qiu, Jose H. Blanchet, Peter W. Glynn
Finite-Sample Regret Bound for Distributionally Robust Offline Tabular Reinforcement Learning. AISTATS (2021)
Zhaonan Qu, Yinyu Ye, Zhengyuan Zhou
Diagonal Preconditioning: Theory and Algorithms. CoRR (2020)
Zhaolin Ren, Aoxiao Zhong, Zhengyuan Zhou, Na Li
Federated LQR: Learning through Sharing. CoRR (2020)
Tianyi Lin, Zhengyuan Zhou, Panayotis Mertikopoulos, Michael I. Jordan
Finite-Time Last-Iterate Convergence for Multi-Agent Learning in Games. CoRR (2020)
Erik Sverdrup, Ayush Kanodia, Zhengyuan Zhou, Susan Athey, Stefan Wager
policytree: Policy learning via doubly robust empirical welfare maximization over trees. J. Open Source Softw. 5 (55) (2020)
Zhimei Ren, Zhengyuan Zhou
Dynamic Batch Learning in High-Dimensional Sparse Linear Contextual Bandits. CoRR (2020)
Yanjun Han, Zhengyuan Zhou, Tsachy Weissman
Optimal No-regret Learning in Repeated First-price Auctions. CoRR (2020)
Yanjun Han, Zhengyuan Zhou, Aaron Flores, Erik Ordentlich, Tsachy Weissman
Learning to Bid Optimally and Efficiently in Adversarial First-price Auctions. CoRR (2020)
Tianyi Lin, Zhengyuan Zhou, Panayotis Mertikopoulos, Michael I. Jordan
Finite-Time Last-Iterate Convergence for Multi-Agent Learning in Games. ICML (2020)
Amélie Héliou, Panayotis Mertikopoulos, Zhengyuan Zhou
Gradient-free Online Learning in Games with Delayed Rewards. CoRR (2020)
Zhaonan Qu, Kaixiang Lin, Jayant Kalagnanam, Zhaojian Li, Jiayu Zhou, Zhengyuan Zhou
Federated Learning's Blessing: FedAvg has Linear Speedup. CoRR (2020)
Chaobing Song, Zhengyuan Zhou, Yichao Zhou, Yong Jiang, Yi Ma
Optimistic Dual Extrapolation for Coherent Non-monotone Variational Inequalities. NeurIPS (2020)
Zhaolin Ren, Zhengyuan Zhou, Linhai Qiu, Ajay Deshpande, Jayant Kalagnanam
Delay-Adaptive Distributed Stochastic Optimization. AAAI (2020)
Yuexiang Zhai, Hermish Mehta, Zhengyuan Zhou, Yi Ma
Understanding l4-based Dictionary Learning: Interpretation, Stability, and Robustness. ICLR (2020)
Zhengyuan Zhou, Jonathan Richard Shewchuk, Dusan M. Stipanovic, Haomiao Huang, Claire J. Tomlin
Smarter Lions: Efficient Cooperative Pursuit in General Bounded Arenas. SIAM J. Control. Optim. 58 (2) (2020)
Amélie Héliou, Panayotis Mertikopoulos, Zhengyuan Zhou
Gradient-free Online Learning in Continuous Games with Delayed Rewards. ICML (2020)
Jose H. Blanchet, Renyuan Xu, Zhengyuan Zhou
Delay-Adaptive Learning in Generalized Linear Contextual Bandits. CoRR (2020)
Yanjun Han, Zhengqing Zhou, Zhengyuan Zhou, Jose H. Blanchet, Peter W. Glynn, Yinyu Ye
Sequential Batch Learning in Finite-Action Linear Contextual Bandits. CoRR (2020)
Xiaoteng Ma, Qiyuan Zhang, Li Xia, Zhengyuan Zhou, Jun Yang, Qianchuan Zhao
Distributional Soft Actor Critic for Risk Sensitive Learning. CoRR (2020)
Nian Si, Fan Zhang, Zhengyuan Zhou, Jose H. Blanchet
Distributional Robust Batch Contextual Bandits. CoRR (2020)
Zhengyuan Zhou, Panayotis Mertikopoulos, Nicholas Bambos, Stephen P. Boyd, Peter W. Glynn
On the Convergence of Mirror Descent beyond Stochastic Convex Programming. SIAM J. Optim. 30 (1) (2020)
Nian Si, Fan Zhang, Zhengyuan Zhou, Jose H. Blanchet
Distributionally Robust Policy Evaluation and Learning in Offline Contextual Bandits. ICML (2020)
Maria Dimakopoulou, Zhengyuan Zhou, Susan Athey, Guido Imbens
Balanced Linear Contextual Bandits. AAAI (2019)
Zhengyuan Zhou, Renyuan Xu, Jose H. Blanchet
Learning in Generalized Linear Contextual Bandits with Stochastic Delays. NeurIPS (2019)
Hao Cheng, Zhengyuan Zhou, Yanqing Li, Wenyi Huang, Jun Feng, Tingfan Tang, Lijun Li
Electrochemiluminescence Sensor Based on Electrospun Three-Dimensional Carbon Nanofibers for the Detection of Difenidol Hydrochloride. Sensors 19 (15) (2019)
Shi Dong, Benjamin Van Roy, Zhengyuan Zhou
Provably Efficient Reinforcement Learning with Aggregated States. CoRR (2019)
Ilai Bistritz, Andrew Ward, Zhengyuan Zhou, Nicholas Bambos
Smart Greedy Distributed Allocation in Microgrids. ICC (2019)
Ilai Bistritz, Zhengyuan Zhou, Xi Chen, Nicholas Bambos, Jose H. Blanchet
Online EXP3 Learning in Adversarial Bandits with Delayed Feedback. NeurIPS (2019)
Panayotis Mertikopoulos, Zhengyuan Zhou
Learning in games with continuous action sets and unknown payoff functions. Math. Program. 173 (1-2) (2019)
Andrew Ward, Zhengyuan Zhou, Nicholas Bambos
Bidding-Based Dynamic Power Pricing Scheme in Smart Grids. ICNC (2019)
Andrew Ward, Zhengyuan Zhou, Nicholas Bambos, Ellen Wang, David Scheinker
Anesthesiologist Surgery Assignments using Policy Learning. ICC (2019)
Daniel Miller, Zhengyuan Zhou, Nicholas Bambos, Irad Ben-Gal
Sensing-Constrained Power Control in Digital Health. ACC (2018)
Lu Jiang, Zhengyuan Zhou, Thomas Leung, Li-Jia Li, Li Fei-Fei
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels. ICML (2018)
Zhengyuan Zhou, Panayotis Mertikopoulos, Nicholas Bambos, Peter W. Glynn, Yinyu Ye, Li-Jia Li, Li Fei-Fei
Distributed Asynchronous Optimization with Unbounded Delays: How Slow Can You Go? ICML (2018)
Zhengyuan Zhou, Susan Athey, Stefan Wager
Offline Multi-Action Policy Learning: Generalization and Optimization. CoRR (2018)
Zhengyuan Zhou, Michael Bloem, Nicholas Bambos
Infinite Time Horizon Maximum Causal Entropy Inverse Reinforcement Learning. IEEE Trans. Autom. Control. 63 (9) (2018)
Andrew Ward, Zhengyuan Zhou, Panayotis Mertikopoulos, Nicholas Bambos
Power Control with Random Delays: Robust Feedback Averaging. CDC (2018)
Maria Dimakopoulou, Zhengyuan Zhou, Susan Athey, Guido Imbens
Balanced Linear Contextual Bandits. CoRR (2018)
Zhengyuan Zhou, Nicholas Bambos, Peter W. Glynn
Deterministic and Stochastic Wireless Network Games: Equilibrium, Dynamics, and Price of Anarchy. Oper. Res. 66 (6) (2018)
Daniel Miller, Zhengyuan Zhou, Nicholas Bambos, Irad Ben-Gal
Optimal Sensing for Patient Health Monitoring. ICC (2018)
Zhengyuan Zhou, Yong Zhou, Dengqing Tang, Kuang Zhao, Tianjiang Hu
Micro-UAV onboard vehicle detection: architecture and experiments. ISR (2018)
Zhengyuan Zhou, Jerry Ding, Haomiao Huang, Ryo Takei, Claire J. Tomlin
Efficient path planning algorithms in reach-avoid problems. Autom. 89 (2018)
Zhengyuan Zhou, Panayotis Mertikopoulos, Susan Athey, Nicholas Bambos, Peter W. Glynn, Yinyu Ye
Learning in Games with Lossy Feedback. NeurIPS (2018)
Saied Mehdian, Zhengyuan Zhou, Nicholas Bambos
Robustness of Join-the-Shortest-Queue Scheduling to Communication Delay. ACC (2018)

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Publication Activity (10 Years)

Top Topics

Top Venues

Zhengyuan Zhou