| 2025 | AISTATS | Statistical Learning of Distributionally Robust Stochastic Control in Continuous State Spaces. | Shengbo Wang, Nian Si, Jose H. Blanchet, Zhengyuan Zhou |
| 2025 | ICLR | Nonconvex Stochastic Optimization under Heavy-Tailed Noises: Optimal Convergence without Gradient Clipping. | Zijian Liu, Zhengyuan Zhou |
| 2025 | ICML | Improved Last-Iterate Convergence of Shuffling Gradient Methods for Nonsmooth Convex Optimization. | Zijian Liu, Zhengyuan Zhou |
| 2025 | ICML | Concurrent Reinforcement Learning with Aggregated States via Randomized Least Squares Value Iteration. | Yan Chen, Qinxun Bai, Yiteng Zhang, Maria Dimakopoulou, Shi Dong, Qi Sun, Zhengyuan Zhou |
| 2025 | ICML | Distributionally Robust Policy Learning under Concept Drifts. | Jingyuan Wang, Zhimei Ren, Ruohan Zhan, Zhengyuan Zhou |
| 2025 | KDD | Surface-based Molecular Design with Multi-modal Flow Matching. | Fang Wu, Zhengyuan Zhou, Shuting Jin, Xiangxiang Zeng, Jure Leskovec, Jinbo Xu |
| 2024 | AISTATS | Feasible Q-Learning for Average Reward Reinforcement Learning. | Ying Jin, Ramki Gummadi, Zhengyuan Zhou, Jose H. Blanchet |
| 2024 | ICLR | Revisiting the Last-Iterate Convergence of Stochastic Gradient Methods. | Zijian Liu, Zhengyuan Zhou |
| 2024 | ICML | On the Convergence of Projected Bures-Wasserstein Gradient Descent under Euclidean Strong Convexity. | Junyi Fan, Yuxuan Han, Zijian Liu, Jian-Feng Cai, Yang Wang, Zhengyuan Zhou |
| 2024 | ICML | Single-Trajectory Distributionally Robust Reinforcement Learning. | Zhipeng Liang, Xiaoteng Ma, Jos H. Blanchet, Jun Yang, Jiheng Zhang, Zhengyuan Zhou |
| 2024 | ICML | On the Last-Iterate Convergence of Shuffling Gradient Methods. | Zijian Liu, Zhengyuan Zhou |
| 2024 | ICML | Adaptively Learning to Select-Rank in Online Platforms. | Jingyuan Wang, Perry Dong, Ying Jin, Ruohan Zhan, Zhengyuan Zhou |
| 2023 | AISTATS | A Finite Sample Complexity Bound for Distributionally Robust Q-learning. | Shengbo Wang, Nian Si, Jos H. Blanchet, Zhengyuan Zhou |
| 2023 | COLT | Breaking the Lower Bound with (Little) Structure: Acceleration in Non-Convex Stochastic Optimization with Heavy-Tailed Noise. | Zijian Liu, Jiawei Zhang, Zhengyuan Zhou |
| 2022 | ICML | Doubly Robust Distributionally Robust Off-Policy Evaluation and Learning. | Nathan Kallus, Xiaojie Mao, Kaiwen Wang, Zhengyuan Zhou |
| 2022 | ICML | Distributionally Robust Q-Learning. | Zijian Liu, Qinxun Bai, Jose H. Blanchet, Perry Dong, Wei Xu, Zhengqing Zhou, Zhengyuan Zhou |
| 2021 | AISTATS | Finite-Sample Regret Bound for Distributionally Robust Offline Tabular Reinforcement Learning. | Zhengqing Zhou, Qinxun Bai, Zhengyuan Zhou, Linhai Qiu, Jose H. Blanchet, Peter W. Glynn |
| 2021 | KDD | MEOW: A Space-Efficient Nonparametric Bid Shading Algorithm. | Wei Zhang, Brendan Kitts, Yanjun Han, Zhengyuan Zhou, Tingyu Mao, Hao He, Shengjun Pan, Aaron Flores, San Gultekin, Tsachy Weissman |
| 2020 | AAAI | Delay-Adaptive Distributed Stochastic Optimization. | Zhaolin Ren, Zhengyuan Zhou, Linhai Qiu, Ajay Deshpande, Jayant Kalagnanam |
| 2020 | ICLR | Understanding l4-based Dictionary Learning: Interpretation, Stability, and Robustness. | Yuexiang Zhai, Hermish Mehta, Zhengyuan Zhou, Yi Ma |
| 2020 | ICML | Gradient-free Online Learning in Continuous Games with Delayed Rewards. | Amlie Hliou, Panayotis Mertikopoulos, Zhengyuan Zhou |
| 2020 | ICML | Finite-Time Last-Iterate Convergence for Multi-Agent Learning in Games. | Tianyi Lin, Zhengyuan Zhou, Panayotis Mertikopoulos, Michael I. Jordan |
| 2020 | ICML | Distributionally Robust Policy Evaluation and Learning in Offline Contextual Bandits. | Nian Si, Fan Zhang, Zhengyuan Zhou, Jose H. Blanchet |
| 2019 | AAAI | Balanced Linear Contextual Bandits. | Maria Dimakopoulou, Zhengyuan Zhou, Susan Athey, Guido Imbens |
| 2018 | ICML | MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels. | Lu Jiang, Zhengyuan Zhou, Thomas Leung, Li-Jia Li, Li Fei-Fei |
| 2018 | ICML | Distributed Asynchronous Optimization with Unbounded Delays: How Slow Can You Go? | Zhengyuan Zhou, Panayotis Mertikopoulos, Nicholas Bambos, Peter W. Glynn, Yinyu Ye, Li-Jia Li, Li Fei-Fei |
| 2017 | CISS | An infinite dimensional model for a many server priority queue. | Neal Master, Zhengyuan Zhou, Nicholas Bambos |
| 2017 | GLOBECOM | Stable Power Control in Wireless Networks via Dual Averaging. | Zhengyuan Zhou, Panayotis Mertikopoulos, Aris L. Moustakas, Saied Mehdian, Nicholas Bambos, Peter W. Glynn |
| 2017 | PIMRC | Longest-queue-first scheduling with intermittent sampling. | Saied Mehdian, Zhengyuan Zhou, Nicholas Bambos |
| 2017 | PIMRC | Least action routing: Identifying the optimal path in a wireless relay network. | Aris L. Moustakas, Panayotis Mertikopoulos, Zhengyuan Zhou, Nick Bambos |
| 2016 | DSAA | Detecting Inaccurate Predictions of Pediatric Surgical Durations. | Zhengyuan Zhou, Daniel Miller, Neal Master, David Scheinker, Nicholas Bambos, Peter W. Glynn |
| 2016 | GLOBECOM | A Stochastic Stability Characterization of the Foschini-Miljanic Algorithm in Random Wireless Networks. | Zhengyuan Zhou, Daniel Miller, Nicholas Bambos, Peter W. Glynn |
| 2015 | GLOBECOM | Scalable Data Center Power Management via a Global Stress Signal. | Daniel Miller, Neal Master, Zhengyuan Zhou, Nicholas Bambos |
| 2014 | AAAI | Hybrid Singular Value Thresholding for Tensor Completion. | Xiaoqin Zhang, Zhengyuan Zhou, Di Wang, Yi Ma |
| 2014 | ICRA | Evasion of a team of dubins vehicles from a hidden pursuer. | Shih-Yuan Liu, Zhengyuan Zhou, Claire J. Tomlin, J. Karl Hedrick |