Zhang, Kaiqing

54 publications

JMLR 2025 Convergence and Sample Complexity of Natural Policy Gradient Primal-Dual Methods for Constrained MDPs Dongsheng Ding, Kaiqing Zhang, Jiali Duan, Tamer Basar, Mihailo R. Jovanovic

ICLR 2025 Do LLM Agents Have Regret? a Case Study in Online Learning and Games Chanwoo Park, Xiangyu Liu, Asuman E. Ozdaglar, Kaiqing Zhang

AAAI 2025 Foundations of Multi-Agent Learning in Dynamic Environments: Where Reinforcement Learning Meets Strategic Decision-Making Kaiqing Zhang

ICLRW 2025 Online Learning with Ranking Feedback and an Application to Equilibrium Computation Mingyang Liu, Yongshan Chen, Zhiyuan Fan, Gabriele Farina, Asuman E. Ozdaglar, Kaiqing Zhang

ICLRW 2024 Do LLM Agents Have Regret? a Case Study in Online Learning and Games Chanwoo Park, Xiangyu Liu, Asuman E. Ozdaglar, Kaiqing Zhang

ICMLW 2024 Do LLM Agents Have Regret? a Case Study in Online Learning and Games Chanwoo Park, Xiangyu Liu, Asuman E. Ozdaglar, Kaiqing Zhang

ICMLW 2024 Do LLM Agents Have Regret? a Case Study in Online Learning and Games Chanwoo Park, Xiangyu Liu, Asuman E. Ozdaglar, Kaiqing Zhang

NeurIPS 2024 Provable Partially Observable Reinforcement Learning with Privileged Information Yang Cai, Xiangyu Liu, Argyris Oikonomou, Kaiqing Zhang

ICMLW 2024 Provable Partially Observable Reinforcement Learning with Privileged Information Yang Cai, Xiangyu Liu, Argyris Oikonomou, Kaiqing Zhang

ICMLW 2024 RLHF from Heterogeneous Feedback via Personalization and Preference Aggregation Chanwoo Park, Mingyang Liu, Dingwen Kong, Kaiqing Zhang, Asuman E. Ozdaglar

ICMLW 2024 RLHF from Heterogeneous Feedback via Personalization and Preference Aggregation Chanwoo Park, Mingyang Liu, Dingwen Kong, Kaiqing Zhang, Asuman E. Ozdaglar

ICLR 2024 Robot Fleet Learning via Policy Merging Lirui Wang, Kaiqing Zhang, Allan Zhou, Max Simchowitz, Russ Tedrake

NeurIPS 2023 A Finite-Sample Analysis of Payoff-Based Independent Learning in Zero-Sum Stochastic Games Zaiwei Chen, Kaiqing Zhang, Eric Mazumdar, Asuman Ozdaglar, Adam Wierman

COLT 2023 Breaking the Curse of Multiagents in a Large State Space: RL in Markov Games with Independent Linear Function Approximation Qiwen Cui, Kaiqing Zhang, Simon Du

ICMLW 2023 Breaking the Curse of Multiagents in a Large State Space: RL in Markov Games with Independent Linear Function Approximation Qiwen Cui, Kaiqing Zhang, Simon Shaolei Du

ICMLW 2023 Breaking the Curse of Multiagents in a Large State Space: RL in Markov Games with Independent Linear Function Approximation Qiwen Cui, Kaiqing Zhang, Simon Shaolei Du

AISTATS 2023 Byzantine-Robust Online and Offline Distributed Reinforcement Learning Yiding Chen, Xuezhou Zhang, Kaiqing Zhang, Mengdi Wang, Xiaojin Zhu

L4DC 2023 Can Direct Latent Model Learning Solve Linear Quadratic Gaussian Control? Yi Tian, Kaiqing Zhang, Russ Tedrake, Suvrit Sra

ICLR 2023 Does Learning from Decentralized Non-IID Unlabeled Data Benefit from Self Supervision? Lirui Wang, Kaiqing Zhang, Yunzhu Li, Yonglong Tian, Russ Tedrake

NeurIPS 2023 Last-Iterate Convergent Policy Gradient Primal-Dual Methods for Constrained MDPs Dongsheng Ding, Chen-Yu Wei, Kaiqing Zhang, Alejandro Ribeiro

ICLR 2023 Learning to Extrapolate: A Transductive Approach Aviv Netanyahu, Abhishek Gupta, Max Simchowitz, Kaiqing Zhang, Pulkit Agrawal

JMLR 2023 Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample Complexity Kaiqing Zhang, Sham M. Kakade, Tamer Basar, Lin F. Yang

NeurIPS 2023 Multi-Player Zero-Sum Markov Games with Networked Separable Interactions Chanwoo Park, Kaiqing Zhang, Asuman Ozdaglar

ICML 2023 Partially Observable Multi-Agent RL with (Quasi-)Efficiency: The Blessing of Information Sharing Xiangyu Liu, Kaiqing Zhang

ICML 2023 Revisiting the Linear-Programming Framework for Offline RL with General Function Approximation Asuman E. Ozdaglar, Sarath Pattathil, Jiawei Zhang, Kaiqing Zhang

NeurIPS 2023 Self-Supervised Reinforcement Learning That Transfers Using Random Features Boyuan Chen, Chuning Zhu, Pulkit Agrawal, Kaiqing Zhang, Abhishek Gupta

AISTATS 2023 Symmetric (Optimistic) Natural Policy Gradient for Multi-Agent Learning with Parameter Convergence Sarath Pattathil, Kaiqing Zhang, Asuman Ozdaglar

COLT 2023 Tackling Combinatorial Distribution Shift: A Matrix Completion Perspective Max Simchowitz, Abhishek Gupta, Kaiqing Zhang

COLT 2023 The Complexity of Markov Equilibrium in Stochastic Games Constantinos Daskalakis, Noah Golowich, Kaiqing Zhang

ICLR 2023 The Power of Regularization in Solving Extensive-Form Games Mingyang Liu, Asuman E. Ozdaglar, Tiancheng Yu, Kaiqing Zhang

ICMLW 2023 Toward Understanding Latent Model Learning in MuZero: A Case Study in Linear Quadratic Gaussian Control Yi Tian, Kaiqing Zhang, Russ Tedrake, Suvrit Sra

ICML 2022 Do Differentiable Simulators Give Better Policy Gradients? Hyung Ju Suh, Max Simchowitz, Kaiqing Zhang, Russ Tedrake

NeurIPS 2022 Globally Convergent Policy Search for Output Estimation Jack Umenberger, Max Simchowitz, Juan Perdomo, Kaiqing Zhang, Russ Tedrake

ICML 2022 Independent Policy Gradient for Large-Scale Markov Potential Games: Sharper Rates, Function Approximation, and Game-Agnostic Convergence Dongsheng Ding, Chen-Yu Wei, Kaiqing Zhang, Mihailo Jovanovic

NeurIPSW 2022 Learning to Extrapolate: A Transductive Approach Aviv Netanyahu, Abhishek Gupta, Max Simchowitz, Kaiqing Zhang, Pulkit Agrawal

ICML 2022 On Improving Model-Free Algorithms for Decentralized Multi-Agent Reinforcement Learning Weichao Mao, Lin Yang, Kaiqing Zhang, Tamer Basar

NeurIPS 2022 What Is a Good Metric to Study Generalization of Minimax Learners? Asuman Ozdaglar, Sarath Pattathil, Jiawei Zhang, Kaiqing Zhang

AAAI 2021 Decentralized Policy Gradient Descent Ascent for Safe Multi-Agent Reinforcement Learning Songtao Lu, Kaiqing Zhang, Tianyi Chen, Tamer Basar, Lior Horesh

NeurIPS 2021 Decentralized Q-Learning in Zero-Sum Markov Games Muhammed Sayin, Kaiqing Zhang, David Leslie, Tamer Basar, Asuman Ozdaglar

NeurIPS 2021 Derivative-Free Policy Optimization for Linear Risk-Sensitive and Robust Control Design: Implicit Regularization and Sample Complexity Kaiqing Zhang, Xiangyuan Zhang, Bin Hu, Tamer Basar

ICLR 2021 Learning Safe Multi-Agent Control with Decentralized Neural Barrier Certificates Zengyi Qin, Kaiqing Zhang, Yuxiao Chen, Jingkai Chen, Chuchu Fan

ICML 2021 Near-Optimal Model-Free Reinforcement Learning in Non-Stationary Episodic MDPs Weichao Mao, Kaiqing Zhang, Ruihao Zhu, David Simchi-Levi, Tamer Basar

ICML 2021 Reinforcement Learning for Cost-Aware Markov Decision Processes Wesley Suttle, Kaiqing Zhang, Zhuoran Yang, Ji Liu, David Kraemer

NeurIPS 2020 An Improved Analysis of (Variance-Reduced) Policy Gradient and Natural Policy Gradient Methods Yanli Liu, Kaiqing Zhang, Tamer Basar, Wotao Yin

NeurIPS 2020 Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample Complexity Kaiqing Zhang, Sham Kakade, Tamer Basar, Lin Yang

NeurIPS 2020 Natural Policy Gradient Primal-Dual Method for Constrained Markov Decision Processes Dongsheng Ding, Kaiqing Zhang, Tamer Basar, Mihailo Jovanovic

NeurIPS 2020 On the Stability and Convergence of Robust Adversarial Reinforcement Learning: A Case Study on Linear Quadratic Systems Kaiqing Zhang, Bin Hu, Tamer Basar

NeurIPS 2020 POLY-HOOT: Monte-Carlo Planning in Continuous Space MDPs with Non-Asymptotic Analysis Weichao Mao, Kaiqing Zhang, Qiaomin Xie, Tamer Basar

L4DC 2020 Policy Optimization for $\mathcal{H}_2$ Linear Control with $\mathcal{H}_\infty$ Robustness Guarantee: Implicit Regularization and Global Convergence Kaiqing Zhang, Bin Hu, Tamer Basar

NeurIPS 2020 Robust Multi-Agent Reinforcement Learning with Model Uncertainty Kaiqing Zhang, Tao Sun, Yunzhe Tao, Sahika Genc, Sunil Mallya, Tamer Basar

NeurIPS 2019 Non-Cooperative Inverse Reinforcement Learning Xiangyuan Zhang, Kaiqing Zhang, Erik Miehling, Tamer Basar

NeurIPS 2019 Policy Optimization Provably Converges to Nash Equilibria in Zero-Sum Linear Quadratic Games Kaiqing Zhang, Zhuoran Yang, Tamer Basar

ICML 2018 Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents Kaiqing Zhang, Zhuoran Yang, Han Liu, Tong Zhang, Tamer Basar

AISTATS 2018 Nonlinear Structured Signal Estimation in High Dimensions via Iterative Hard Thresholding Kaiqing Zhang, Zhuoran Yang, Zhaoran Wang