A general, open-loop formulation for reach-avoid games. - Zhengyuan Zhou; Ryo Takei; Haomiao Huang; Claire J. Tomlin (CDC, 2012)

Evasion as a team against a faster pursuer. - Shih-Yuan Liu; Zhengyuan Zhou; Claire J. Tomlin; J. Karl Hedrick (ACC, 2013)

Simultaneous Rectification and Alignment via Robust Recovery of Low-rank Tensors. - Xiaoqin Zhang 002; Di Wang 008; Zhengyuan Zhou; Yi Ma 001 (NIPS, 2013)

Hybrid Singular Value Thresholding for Tensor Completion. - Xiaoqin Zhang 002; Zhengyuan Zhou; Di Wang 008; Yi Ma 001 (AAAI, 2014)

Multiplayer reach-avoid games via low dimensional solutions and maximum matching. - Mo Chen 001; Zhengyuan Zhou; Claire J. Tomlin (ACC, 2014)

Convexity verification for a hybrid chance constrained method in stochastic control problems. - Zhengyuan Zhou; Michael P. Vitus; Claire J. Tomlin (ACC, 2014)

A path defense approach to the multiplayer reach-avoid game. - Mo Chen 001; Zhengyuan Zhou; Claire J. Tomlin (CDC, 2014)

Evasion of a team of dubins vehicles from a hidden pursuer. - Shih-Yuan Liu; Zhengyuan Zhou; Claire J. Tomlin; J. Karl Hedrick (ICRA, 2014)

Distributed Multi-Depot Routing without Communications. - Dawsen Hwang; Patrick Jaillet; Zhengyuan Zhou (CoRR, 2014)

A general model for resource allocation in utility computing. - Zhengyuan Zhou; Nicholas Bambos (ACC, 2015)

Wireless communications games in fixed and random environments. - Zhengyuan Zhou; Nicholas Bambos (CDC, 2015)

Target-rate driven resource sharing in queueing systems. - Zhengyuan Zhou; Nicholas Bambos (CDC, 2015)

Scalable Data Center Power Management via a Global Stress Signal. - Daniel Miller 001; Neal Master; Zhengyuan Zhou; Nicholas Bambos (GLOBECOM, 2015)

A game-theoretical formulation of influence networks. - Zhengyuan Zhou; Benjamin Yolken; Reiko Ann Miura-Ko; Nicholas Bambos (ACC, 2016)

Repeated games for power control in wireless communications: Equilibrium and regret. - Zhengyuan Zhou; Peter W. Glynn; Nicholas Bambos (CDC, 2016)

Detecting Inaccurate Predictions of Pediatric Surgical Durations. - Zhengyuan Zhou; Daniel Miller 001; Neal Master; David Scheinker; Nicholas Bambos; Peter W. Glynn (DSAA, 2016)

Dynamics on Linear Influence Network Games Under Stochastic Environments. - Zhengyuan Zhou; Nicholas Bambos; Peter W. Glynn (GameSec, 2016)

A Stochastic Stability Characterization of the Foschini-Miljanic Algorithm in Random Wireless Networks. - Zhengyuan Zhou; Daniel Miller 001; Nicholas Bambos; Peter W. Glynn (GLOBECOM, 2016)

Cooperative pursuit with Voronoi partitions. - Zhengyuan Zhou; Wei Zhang 013; Jerry Ding; Haomiao Huang; Dusan M. Stipanovic; Claire J. Tomlin (Autom., 2016)

The Importance of Exploration in Online Marketplaces. - Siddhartha Banerjee; Ramesh Johari; Zhengyuan Zhou (IEEE Internet Comput., 2016)

An infinite dimensional model for a single server priority queue. - Neal Master; Zhengyuan Zhou; Nicholas Bambos (ACC, 2017)

Join-the-shortest-queue scheduling with delay. - Saied Mehdian; Zhengyuan Zhou; Nicholas Bambos (ACC, 2017)

Asynchronous best-response dynamics for resource allocation games in cloud computing. - Kevin Schubert; Neal Master; Zhengyuan Zhou; Nicholas Bambos (ACC, 2017)

Mirror descent learning in continuous games. - Zhengyuan Zhou; Panayotis Mertikopoulos; Aris L. Moustakas; Nicholas Bambos; Peter W. Glynn (CDC, 2017)

An infinite dimensional model for a many server priority queue. - Neal Master; Zhengyuan Zhou; Nicholas Bambos (CISS, 2017)

Stable Power Control in Wireless Networks via Dual Averaging. - Zhengyuan Zhou; Panayotis Mertikopoulos; Aris L. Moustakas; Saied Mehdian; Nicholas Bambos; Peter W. Glynn (GLOBECOM, 2017)

Dynamic control of data center network and computation resources. - Daniel Miller 001; Li Xia; Zhengyuan Zhou; Nicholas Bambos (ICNC, 2017)

Stochastic Mirror Descent in Variationally Coherent Optimization Problems. - Zhengyuan Zhou; Panayotis Mertikopoulos; Nicholas Bambos; Stephen P. Boyd; Peter W. Glynn (NIPS, 2017)

Countering Feedback Delays in Multi-Agent Learning. - Zhengyuan Zhou; Panayotis Mertikopoulos; Nicholas Bambos; Peter W. Glynn; Claire J. Tomlin (NIPS, 2017)

Longest-queue-first scheduling with intermittent sampling. - Saied Mehdian; Zhengyuan Zhou; Nicholas Bambos (PIMRC, 2017)

Least action routing: Identifying the optimal path in a wireless relay network. - Aris L. Moustakas; Panayotis Mertikopoulos; Zhengyuan Zhou; Nick Bambos (PIMRC, 2017)

Mirror descent in non-convex stochastic programming. - Zhengyuan Zhou; Panayotis Mertikopoulos; Nicholas Bambos; Stephen P. Boyd; Peter W. Glynn (CoRR, 2017)

MentorNet: Regularizing Very Deep Neural Networks on Corrupted Labels. - Lu Jiang 004; Zhengyuan Zhou; Thomas Leung; Li-Jia Li 001; Li Fei-Fei 001 (CoRR, 2017)

Improving predictions of pediatric surgical durations with supervised learning. - Neal Master; Zhengyuan Zhou; Daniel Miller 001; David Scheinker; Nicholas Bambos; Peter W. Glynn (Int. J. Data Sci. Anal., 2017)

Multiplayer Reach-Avoid Games via Pairwise Outcomes. - Mo Chen 001; Zhengyuan Zhou; Claire J. Tomlin (IEEE Trans. Autom. Control., 2017)

Service Rate Control of Tandem Queues With Power Constraints. - Li Xia; Daniel Miller 001; Zhengyuan Zhou; Nicholas Bambos (IEEE Trans. Autom. Control., 2017)

Robustness of Join-the-Shortest-Queue Scheduling to Communication Delay. - Saied Mehdian; Zhengyuan Zhou; Nicholas Bambos (ACC, 2018)

Sensing-Constrained Power Control in Digital Health. - Daniel Miller 001; Zhengyuan Zhou; Nicholas Bambos; Irad Ben-Gal (ACC, 2018)

Power Control with Random Delays: Robust Feedback Averaging. - Andrew Ward; Zhengyuan Zhou; Panayotis Mertikopoulos; Nicholas Bambos (CDC, 2018)

Optimal Sensing for Patient Health Monitoring. - Daniel Miller 001; Zhengyuan Zhou; Nicholas Bambos; Irad Ben-Gal (ICC, 2018)

MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels. - Lu Jiang 004; Zhengyuan Zhou; Thomas Leung; Li-Jia Li 001; Li Fei-Fei 001 (ICML, 2018)

Distributed Asynchronous Optimization with Unbounded Delays: How Slow Can You Go? - Zhengyuan Zhou; Panayotis Mertikopoulos; Nicholas Bambos; Peter W. Glynn; Yinyu Ye 001; Li-Jia Li 001; Li Fei-Fei 001 (ICML, 2018)

Micro-UAV onboard vehicle detection: architecture and experiments. - Zhengyuan Zhou; Yong Zhou; Dengqing Tang; Kuang Zhao; Tianjiang Hu (ISR, 2018)

Learning in Games with Lossy Feedback. - Zhengyuan Zhou; Panayotis Mertikopoulos; Susan Athey; Nicholas Bambos; Peter W. Glynn; Yinyu Ye 001 (NeurIPS, 2018)

Efficient path planning algorithms in reach-avoid problems. - Zhengyuan Zhou; Jerry Ding; Haomiao Huang; Ryo Takei; Claire J. Tomlin (Autom., 2018)

Deterministic and Stochastic Wireless Network Games: Equilibrium, Dynamics, and Price of Anarchy. - Zhengyuan Zhou; Nicholas Bambos; Peter W. Glynn (Oper. Res., 2018)

Infinite Time Horizon Maximum Causal Entropy Inverse Reinforcement Learning. - Zhengyuan Zhou; Michael Bloem; Nicholas Bambos (IEEE Trans. Autom. Control., 2018)

Balanced Linear Contextual Bandits. - Maria Dimakopoulou; Zhengyuan Zhou; Susan Athey; Guido Imbens (AAAI, 2019)

Smart Greedy Distributed Allocation in Microgrids. - Ilai Bistritz; Andrew Ward; Zhengyuan Zhou; Nicholas Bambos (ICC, 2019)

Anesthesiologist Surgery Assignments using Policy Learning. - Andrew Ward; Zhengyuan Zhou; Nicholas Bambos; Ellen Wang; David Scheinker (ICC, 2019)

Bidding-Based Dynamic Power Pricing Scheme in Smart Grids. - Andrew Ward; Zhengyuan Zhou; Nicholas Bambos (ICNC, 2019)

Online EXP3 Learning in Adversarial Bandits with Delayed Feedback. - Ilai Bistritz; Zhengyuan Zhou; Xi Chen; Nicholas Bambos; Jose H. Blanchet (NeurIPS, 2019)

Learning in Generalized Linear Contextual Bandits with Stochastic Delays. - Zhengyuan Zhou; Renyuan Xu; Jose H. Blanchet (NeurIPS, 2019)

Provably Efficient Reinforcement Learning with Aggregated States. - Shi Dong 003; Benjamin Van Roy; Zhengyuan Zhou (CoRR, 2019)

Learning in games with continuous action sets and unknown payoff functions. - Panayotis Mertikopoulos; Zhengyuan Zhou (Math. Program., 2019)

Electrochemiluminescence Sensor Based on Electrospun Three-Dimensional Carbon Nanofibers for the Detection of Difenidol Hydrochloride. - Hao Cheng; Zhengyuan Zhou; Yanqing Li; Wenyi Huang; Jun Feng; Tingfan Tang; Lijun Li (Sensors, 2019)

Delay-Adaptive Distributed Stochastic Optimization. - Zhaolin Ren; Zhengyuan Zhou; Linhai Qiu; Ajay Deshpande; Jayant Kalagnanam (AAAI, 2020)

Understanding l4-based Dictionary Learning: Interpretation, Stability, and Robustness. - Yuexiang Zhai; Hermish Mehta; Zhengyuan Zhou; Yi Ma 001 (ICLR, 2020)

Gradient-free Online Learning in Continuous Games with Delayed Rewards. - Amélie Héliou; Panayotis Mertikopoulos; Zhengyuan Zhou (ICML, 2020)

Finite-Time Last-Iterate Convergence for Multi-Agent Learning in Games. - Tianyi Lin; Zhengyuan Zhou; Panayotis Mertikopoulos; Michael I. Jordan (ICML, 2020)

Distributionally Robust Policy Evaluation and Learning in Offline Contextual Bandits. - Nian Si; Fan Zhang 059; Zhengyuan Zhou; Jose H. Blanchet (ICML, 2020)

Optimistic Dual Extrapolation for Coherent Non-monotone Variational Inequalities. - Chaobing Song; Zhengyuan Zhou; Yichao Zhou 003; Yong Jiang 001; Yi Ma 001 (NeurIPS, 2020)

Diagonal Preconditioning: Theory and Algorithms. - Zhaonan Qu; Yinyu Ye 001; Zhengyuan Zhou (CoRR, 2020)

Sequential Batch Learning in Finite-Action Linear Contextual Bandits. - Yanjun Han; Zhengqing Zhou; Zhengyuan Zhou; Jose H. Blanchet; Peter W. Glynn; Yinyu Ye 001 (CoRR, 2020)

Distributional Soft Actor Critic for Risk Sensitive Learning. - Xiaoteng Ma; Qiyuan Zhang; Li Xia; Zhengyuan Zhou; Jun Yang 028; Qianchuan Zhao (CoRR, 2020)

Distributional Robust Batch Contextual Bandits. - Nian Si; Fan Zhang 059; Zhengyuan Zhou; Jose H. Blanchet (CoRR, 2020)

Gradient-free Online Learning in Games with Delayed Rewards. - Amélie Héliou; Panayotis Mertikopoulos; Zhengyuan Zhou (CoRR, 2020)

Learning to Bid Optimally and Efficiently in Adversarial First-price Auctions. - Yanjun Han; Zhengyuan Zhou; Aaron Flores 001; Erik Ordentlich; Tsachy Weissman (CoRR, 2020)

Federated Learning's Blessing: FedAvg has Linear Speedup. - Zhaonan Qu; Kaixiang Lin; Jayant Kalagnanam; Zhaojian Li; Jiayu Zhou; Zhengyuan Zhou (CoRR, 2020)

Federated LQR: Learning through Sharing. - Zhaolin Ren; Aoxiao Zhong; Zhengyuan Zhou; Na Li 002 (CoRR, 2020)

policytree: Policy learning via doubly robust empirical welfare maximization over trees. - Erik Sverdrup; Ayush Kanodia; Zhengyuan Zhou; Susan Athey; Stefan Wager (J. Open Source Softw., 2020)

Smarter Lions: Efficient Cooperative Pursuit in General Bounded Arenas. - Zhengyuan Zhou; Jonathan Richard Shewchuk; Dusan M. Stipanovic; Haomiao Huang; Claire J. Tomlin (SIAM J. Control. Optim., 2020)

On the Convergence of Mirror Descent beyond Stochastic Convex Programming. - Zhengyuan Zhou; Panayotis Mertikopoulos; Nicholas Bambos; Stephen P. Boyd; Peter W. Glynn (SIAM J. Optim., 2020)

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 (AISTATS, 2021)

MEOW: A Space-Efficient Nonparametric Bid Shading Algorithm. - Wei Zhang; Brendan Kitts; Yanjun Han; Zhengyuan Zhou; Tingyu Mao; Hao He; Shengjun Pan; Aaron Flores 001; San Gultekin; Tsachy Weissman (KDD, 2021)

Provably Sample Efficient Reinforcement Learning in Competitive Linear Quadratic Systems. - Jingwei Zhang; Zhuoran Yang; Zhengyuan Zhou; Zhaoran Wang 001 (L4DC, 2021)

Online Multi-Armed Bandits with Adaptive Inference. - Maria Dimakopoulou; Zhimei Ren; Zhengyuan Zhou (NeurIPS, 2021)

Simple Agent, Complex Environment: Efficient Reinforcement Learning with Agent State. - Shi Dong 003; Benjamin Van Roy; Zhengyuan Zhou (CoRR, 2021)

Doubly-Adaptive Thompson Sampling for Multi-Armed and Contextual Bandits. - Maria Dimakopoulou; Zhimei Ren; Zhengyuan Zhou (CoRR, 2021)

No Discounted-Regret Learning in Adversarial Bandits with Delays. - Ilai Bistritz; Zhengyuan Zhou; Xi Chen; Nicholas Bambos; Jose H. Blanchet (CoRR, 2021)

Computational Benefits of Intermediate Rewards for Hierarchical Planning. - Yuexiang Zhai; Christina Baek; Zhengyuan Zhou; Jiantao Jiao; Yi Ma 001 (CoRR, 2021)

Optimal No-Regret Learning in Strongly Monotone Games with Bandit Feedback. - Tianyi Lin; Zhengyuan Zhou; Wenjia Ba; Jiawei Zhang (CoRR, 2021)

Robust Power Management via Learning and Game Design. - Zhengyuan Zhou; Panayotis Mertikopoulos; Aris L. Moustakas; Nicholas Bambos; Peter W. Glynn (Oper. Res., 2021)

Robust Low-Rank Tensor Recovery with Rectification and Alignment. - Xiaoqin Zhang 002; Di Wang 008; Zhengyuan Zhou; Yi Ma 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2021)

Doubly Robust Distributionally Robust Off-Policy Evaluation and Learning. - Nathan Kallus; Xiaojie Mao; Kaiwen Wang; Zhengyuan Zhou (ICML, 2022)

Distributionally Robust Q-Learning. - Zijian Liu 003; Qinxun Bai; Jose H. Blanchet; Perry Dong; Wei Xu 017; Zhengqing Zhou; Zhengyuan Zhou (ICML, 2022)

Society of Agents: Regret Bounds of Concurrent Thompson Sampling. - Yan Chen; Perry Dong; Qinxun Bai; Maria Dimakopoulou; Wei Xu 017; Zhengyuan Zhou (NeurIPS, 2022)

Leveraging the Hints: Adaptive Bidding in Repeated First-Price Auctions. - Wei Zhang; Yanjun Han; Zhengyuan Zhou; Aaron Flores 001; Tsachy Weissman (NeurIPS, 2022)

Optimal Diagonal Preconditioning: Theory and Practice. - Zhaonan Qu; Wenzhi Gao; Oliver Hinder; Yinyu Ye 001; Zhengyuan Zhou (CoRR, 2022)

Distributionally Robust Offline Reinforcement Learning with Linear Function Approximation. - Xiaoteng Ma; Zhipeng Liang; Jose H. Blanchet; Mingwen Liu; Li Xia; Jiheng Zhang; Qianchuan Zhao; Zhengyuan Zhou (CoRR, 2022)

Batched Learning in Generalized Linear Contextual Bandits With General Decision Sets. - Zhimei Ren; Zhengyuan Zhou; Jayant R. Kalagnanam (IEEE Control. Syst. Lett., 2022)

Computational Benefits of Intermediate Rewards for Goal-Reaching Policy Learning. - Yuexiang Zhai; Christina Baek; Zhengyuan Zhou; Jiantao Jiao; Yi Ma 001 (J. Artif. Intell. Res., 2022)

No Weighted-Regret Learning in Adversarial Bandits with Delays. - Ilai Bistritz; Zhengyuan Zhou; Xi Chen; Nicholas Bambos; José H. Blanchet (J. Mach. Learn. Res., 2022)

Simple Agent, Complex Environment: Efficient Reinforcement Learning with Agent States. - Shi Dong 003; Benjamin Van Roy; Zhengyuan Zhou (J. Mach. Learn. Res., 2022)

Distributed Stochastic Optimization with Large Delays. - Zhengyuan Zhou; Panayotis Mertikopoulos; Nicholas Bambos; Peter W. Glynn; Yinyu Ye 001 (Math. Oper. Res., 2022)

Smart Greedy Distributed Energy Allocation: A Random Games Approach. - Ilai Bistritz; Andrew Ward; Zhengyuan Zhou; Nicholas Bambos (IEEE Trans. Autom. Control., 2022)

A Finite Sample Complexity Bound for Distributionally Robust Q-learning. - Shengbo Wang; Nian Si; José H. Blanchet; Zhengyuan Zhou (AISTATS, 2023)

Breaking the Lower Bound with (Little) Structure: Acceleration in Non-Convex Stochastic Optimization with Heavy-Tailed Noise. - Zijian Liu 003; Jiawei Zhang; Zhengyuan Zhou (COLT, 2023)

Single-Trajectory Distributionally Robust Reinforcement Learning. - Zhipeng Liang; Xiaoteng Ma; Jose H. Blanchet; Jiheng Zhang; Zhengyuan Zhou (CoRR, 2023)

Near-Optimal High-Probability Convergence for Non-Convex Stochastic Optimization with Variance Reduction. - Zijian Liu 003; Perry Dong; Srikanth Jagabathula; Zhengyuan Zhou (CoRR, 2023)

Stochastic Nonsmooth Convex Optimization with Heavy-Tailed Noises. - Zijian Liu 003; Zhengyuan Zhou (CoRR, 2023)

Sample Complexity of Variance-reduced Distributionally Robust Q-learning. - Shengbo Wang; Nian Si; Jose H. Blanchet; Zhengyuan Zhou (CoRR, 2023)

On the Foundation of Distributionally Robust Reinforcement Learning. - Shengbo Wang; Nian Si; Jose H. Blanchet; Zhengyuan Zhou (CoRR, 2023)

A Unified Linear Speedup Analysis of Federated Averaging and Nesterov FedAvg. - Zhaonan Qu; Kaixiang Lin; Zhaojian Li; Jiayu Zhou; Zhengyuan Zhou (J. Artif. Intell. Res., 2023)

Offline Multi-Action Policy Learning: Generalization and Optimization. - Zhengyuan Zhou; Susan Athey; Stefan Wager (Oper. Res., 2023)

Structured Sparsity Optimization With Non-Convex Surrogates of $ ell _{2,0}$ℓ2,0-Norm: A Unified Algorithmic Framework. - Xiaoqin Zhang 002; Jingjing Zheng; Di Wang 008; Guiying Tang; Zhengyuan Zhou; Zhouchen Lin (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Distributionally Robust Batch Contextual Bandits. - Nian Si; Fan Zhang 059; Zhengyuan Zhou; Jose H. Blanchet (Manag. Sci., 2023)

Feasible Q-Learning for Average Reward Reinforcement Learning. - Ying Jin; Ramki Gummadi; Zhengyuan Zhou; Jose H. Blanchet (AISTATS, 2024)

Revisiting the Last-Iterate Convergence of Stochastic Gradient Methods. - Zijian Liu 003; Zhengyuan Zhou (ICLR, 2024)

On the Convergence of Projected Bures-Wasserstein Gradient Descent under Euclidean Strong Convexity. - Junyi Fan; Yuxuan Han; Zijian Liu 003; Jian-Feng Cai 001; Yang Wang 020; Zhengyuan Zhou (ICML, 2024)

Single-Trajectory Distributionally Robust Reinforcement Learning. - Zhipeng Liang; Xiaoteng Ma; José H. Blanchet; Jun Yang 028; Jiheng Zhang; Zhengyuan Zhou (ICML, 2024)

On the Last-Iterate Convergence of Shuffling Gradient Methods. - Zijian Liu 003; Zhengyuan Zhou (ICML, 2024)

Adaptively Learning to Select-Rank in Online Platforms. - Jingyuan Wang; Perry Dong; Ying Jin; Ruohan Zhan; Zhengyuan Zhou (ICML, 2024)

Stochastic contextual bandits with graph feedback: from independence number to MAS number. - Yuxiao Wen; Yanjun Han; Zhengyuan Zhou (NeurIPS, 2024)

Simulation-Based Benchmarking of Reinforcement Learning Agents for Personalized Retail Promotions. - Yu Xia; Sriram Narayanamoorthy; Zhengyuan Zhou; Joshua Mabry (CoRR, 2024)

Distributionally Robust Policy Learning under Concept Drifts. - Jingyuan Wang; Zhimei Ren; Ruohan Zhan; Zhengyuan Zhou (CoRR, 2024)

Learning to Order for Inventory Systems with Lost Sales and Uncertain Supplies. - Boxiao Chen; Jiashuo Jiang; Jiawei Zhang 006; Zhengyuan Zhou (Manag. Sci., 2024)

Dynamic Batch Learning in High-Dimensional Sparse Linear Contextual Bandits. - Zhimei Ren; Zhengyuan Zhou (Manag. Sci., 2024)

Policy Learning with Adaptively Collected Data. - Ruohan Zhan; Zhimei Ren; Susan Athey; Zhengyuan Zhou (Manag. Sci., 2024)

Delay-Adaptive Learning in Generalized Linear Contextual Bandits. - José H. Blanchet; Renyuan Xu; Zhengyuan Zhou (Math. Oper. Res., 2024)

Tensor Recovery With Weighted Tensor Average Rank. - Xiaoqin Zhang 002; Jingjing Zheng; Li Zhao 005; Zhengyuan Zhou; Zhouchen Lin (IEEE Trans. Neural Networks Learn. Syst., 2024)

RED-Net: Residual and Enhanced Discriminative Network for Image Steganalysis in the Internet of Medical Things and Telemedicine. - Kai Chen; Zhengyuan Zhou; Yuchen Li; Xu Ji; Jiasong Wu; Jean-Louis Coatrieux; Yang Chen 008; Gouenou Coatrieux (IEEE J. Biomed. Health Informatics, 2024)

Global texture sensitive convolutional transformer for medical image steganalysis. - Zhengyuan Zhou; Kai Chen; Dianlin Hu; Huazhong Shu; Gouenou Coatrieux; Jean-Louis Coatrieux; Yang Chen 008 (Multim. Syst., 2024)

Statistical Learning of Distributionally Robust Stochastic Control in Continuous State Spaces. - Shengbo Wang; Nian Si; Jose H. Blanchet; Zhengyuan Zhou (AISTATS, 2025)

Nonconvex Stochastic Optimization under Heavy-Tailed Noises: Optimal Convergence without Gradient Clipping. - Zijian Liu 003; Zhengyuan Zhou (ICLR, 2025)

TIGC-Net: Transformer-Improved Graph Convolution Network for spatio-temporal prediction. - Kai Chen; Zhengyuan Zhou; Yao Liu; Tianjiao Ji; Weiya Sun; Chunfeng Yang; Yang Chen 008; Xiao Lu (Biomed. Signal Process. Control., 2025)

Optimal No-Regret Learning in Repeated First-Price Auctions. - Yanjun Han; Tsachy Weissman; Zhengyuan Zhou (Oper. Res., 2025)

Adaptive, Doubly Optimal No-Regret Learning in Strongly Monotone and Exp-Concave Games with Gradient Feedback. - Michael I. Jordan; Tianyi Lin; Zhengyuan Zhou (Oper. Res., 2025)

Optimal Diagonal Preconditioning. - Zhaonan Qu; Wenzhi Gao; Oliver Hinder; Yinyu Ye 001; Zhengyuan Zhou (Oper. Res., 2025)

DSAC: Distributional Soft Actor-Critic for Risk-Sensitive Reinforcement Learning. - Xiaoteng Ma; Junyao Chen; Li Xia; Jun Yang 028; Qianchuan Zhao; Zhengyuan Zhou (J. Artif. Intell. Res., 2025)

Learning to Bid in Non-Stationary Repeated First-Price Auctions. - Zihao Hu; Xiaoyu Fan; Yuan Yao 011; Jiheng Zhang; Zhengyuan Zhou (CoRR, 2025)

Concurrent Learning with Aggregated States via Randomized Least Squares Value Iteration. - Yan Chen; Qinxun Bai; Yiteng Zhang; Shi Dong; Maria Dimakopoulou; Qi Sun; Zhengyuan Zhou (CoRR, 2025)

Learning an Optimal Assortment Policy under Observational Data. - Yuxuan Han; Han Zhong 001; Miao Lu; Jose H. Blanchet; Zhengyuan Zhou (CoRR, 2025)

Joint Value Estimation and Bidding in Repeated First-Price Auctions. - Yuxiao Wen; Yanjun Han; Zhengyuan Zhou (CoRR, 2025)

Improved Last-Iterate Convergence of Shuffling Gradient Methods for Nonsmooth Convex Optimization. - Zijian Liu; Zhengyuan Zhou (CoRR, 2025)

DR-SAC: Distributionally Robust Soft Actor-Critic for Reinforcement Learning under Uncertainty. - Mingxuan Cui; Duo Zhou; Yuxuan Han; Grani A. Hanasusanto; Qiong Wang; Huan Zhang 001; Zhengyuan Zhou (CoRR, 2025)