Kaiqing Zhang

ORCID

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 127

Top Venues

Publications

Lirui Wang, Kaiqing Zhang, Allan Zhou, Max Simchowitz, Russ Tedrake
Robot Fleet Learning via Policy Merging. ICLR (2024)
Chanwoo Park, Mingyang Liu, Dingwen Kong, Kaiqing Zhang, Asuman E. Ozdaglar
RLHF from Heterogeneous Feedback via Personalization and Preference Aggregation. CoRR (2024)
Chanwoo Park, Xiangyu Liu, Asuman E. Ozdaglar, Kaiqing Zhang
Do LLM Agents Have Regret? A Case Study in Online Learning and Games. CoRR (2024)
Yi Tian, Kaiqing Zhang, Russ Tedrake, Suvrit Sra
Toward Understanding State Representation Learning in MuZero: A Case Study in Linear Quadratic Gaussian Control. CDC (2023)
Qiwen Cui, Kaiqing Zhang, Simon S. Du
Breaking the Curse of Multiagents in a Large State Space: RL in Markov Games with Independent Linear Function Approximation. CoRR (2023)
Dongsheng Ding, Chen-Yu Wei, Kaiqing Zhang, Alejandro Ribeiro
Last-Iterate Convergent Policy Gradient Primal-Dual Methods for Constrained MDPs. CoRR (2023)
Boyuan Chen, Chuning Zhu, Pulkit Agrawal, Kaiqing Zhang, Abhishek Gupta
Self-Supervised Reinforcement Learning that Transfers using Random Features. CoRR (2023)
Xiangyu Liu, Kaiqing Zhang
Partially Observable Multi-agent RL with (Quasi-)Efficiency: The Blessing of Information Sharing. ICML (2023)
Boyuan Chen, Chuning Zhu, Pulkit Agrawal, Kaiqing Zhang, Abhishek Gupta
Self-Supervised Reinforcement Learning that Transfers using Random Features. NeurIPS (2023)
Zaiwei Chen, Kaiqing Zhang, Eric Mazumdar, Asuman E. Ozdaglar, Adam Wierman
A Finite-Sample Analysis of Payoff-Based Independent Learning in Zero-Sum Stochastic Games. NeurIPS (2023)
Lirui Wang, Kaiqing Zhang, Yunzhu Li, Yonglong Tian, Russ Tedrake
Does Learning from Decentralized Non-IID Unlabeled Data Benefit from Self Supervision? ICLR (2023)
Lirui Wang, Kaiqing Zhang, Allan Zhou, Max Simchowitz, Russ Tedrake
Fleet Policy Learning via Weight Merging and An Application to Robotic Tool-Use. CoRR (2023)
Yi Tian, Kaiqing Zhang, Russ Tedrake, Suvrit Sra
Can Direct Latent Model Learning Solve Linear Quadratic Gaussian Control? L4DC (2023)
Han Shen, Kaiqing Zhang, Mingyi Hong, Tianyi Chen
Towards Understanding Asynchronous Advantage Actor-Critic: Convergence and Linear Speedup. IEEE Trans. Signal Process. 71 (2023)
Max Simchowitz, Abhishek Gupta, Kaiqing Zhang
Tackling Combinatorial Distribution Shift: A Matrix Completion Perspective. CoRR (2023)
Chanwoo Park, Kaiqing Zhang, Asuman E. Ozdaglar
Multi-Player Zero-Sum Markov Games with Networked Separable Interactions. NeurIPS (2023)
Bin Hu, Kaiqing Zhang, Na Li, Mehran Mesbahi, Maryam Fazel, Tamer Basar
Toward a Theoretical Foundation of Policy Optimization for Learning Control Policies. Annu. Rev. Control. Robotics Auton. Syst. 6 (2023)
Yiding Chen, Xuezhou Zhang, Kaiqing Zhang, Mengdi Wang, Xiaojin Zhu
Byzantine-Robust Online and Offline Distributed Reinforcement Learning. AISTATS (2023)
Constantinos Daskalakis, Noah Golowich, Kaiqing Zhang
The Complexity of Markov Equilibrium in Stochastic Games. COLT (2023)
Xiangyu Liu, Kaiqing Zhang
Partially Observable Multi-agent RL with (Quasi-)Efficiency: The Blessing of Information Sharing. CoRR (2023)
Dongsheng Ding, Chen-Yu Wei, Kaiqing Zhang, Alejandro Ribeiro
Last-Iterate Convergent Policy Gradient Primal-Dual Methods for Constrained MDPs. NeurIPS (2023)
Zaiwei Chen, Kaiqing Zhang, Eric Mazumdar, Asuman E. Ozdaglar, Adam Wierman
A Finite-Sample Analysis of Payoff-Based Independent Learning in Zero-Sum Stochastic Games. CoRR (2023)
Zaiwei Chen, Kaiqing Zhang, Eric Mazumdar, Asuman E. Ozdaglar, Adam Wierman
Two-Timescale Q-Learning with Function Approximation in Zero-Sum Stochastic Games. CoRR (2023)
Chanwoo Park, Kaiqing Zhang, Asuman E. Ozdaglar
Multi-Player Zero-Sum Markov Games with Networked Separable Interactions. CoRR (2023)
Aviv Netanyahu, Abhishek Gupta, Max Simchowitz, Kaiqing Zhang, Pulkit Agrawal
Learning to Extrapolate: A Transductive Approach. ICLR (2023)
Aviv Netanyahu, Abhishek Gupta, Max Simchowitz, Kaiqing Zhang, Pulkit Agrawal
Learning to Extrapolate: A Transductive Approach. CoRR (2023)
Qiwen Cui, Kaiqing Zhang, Simon S. Du
Breaking the Curse of Multiagents in a Large State Space: RL in Markov Games with Independent Linear Function Approximation. COLT (2023)
Mingyang Liu, Asuman E. Ozdaglar, Tiancheng Yu, Kaiqing Zhang
The Power of Regularization in Solving Extensive-Form Games. ICLR (2023)
Max Simchowitz, Abhishek Gupta, Kaiqing Zhang
Tackling Combinatorial Distribution Shift: A Matrix Completion Perspective. COLT (2023)
Asuman E. Ozdaglar, Sarath Pattathil, Jiawei Zhang, Kaiqing Zhang
Revisiting the Linear-Programming Framework for Offline RL with General Function Approximation. ICML (2023)
Sarath Pattathil, Kaiqing Zhang, Asuman E. Ozdaglar
Symmetric (Optimistic) Natural Policy Gradient for Multi-Agent Learning with Parameter Convergence. AISTATS (2023)
Kaiqing Zhang, Sham M. Kakade, Tamer Basar, Lin F. Yang
Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample Complexity. J. Mach. Learn. Res. 24 (2023)
Muhammed O. Sayin, Kaiqing Zhang, Asuman E. Ozdaglar
Fictitious Play in Markov Games with Single Controller. EC (2022)
Asuman E. Ozdaglar, Sarath Pattathil, Jiawei Zhang, Kaiqing Zhang
Revisiting the Linear-Programming Framework for Offline RL with General Function Approximation. CoRR (2022)
Bin Hu, Kaiqing Zhang, Na Li, Mehran Mesbahi, Maryam Fazel, Tamer Basar
Towards a Theoretical Foundation of Policy Optimization for Learning Control Policies. CoRR (2022)
Lujie Yang, Kaiqing Zhang, Alexandre Amice, Yunzhu Li, Russ Tedrake
Discrete Approximate Information States in Partially Observable Environments. ACC (2022)
Yi Tian, Kaiqing Zhang, Russ Tedrake, Suvrit Sra
Can Direct Latent Model Learning Solve Linear Quadratic Gaussian Control? CoRR (2022)
Dongsheng Ding, Chen-Yu Wei, Kaiqing Zhang, Mihailo R. Jovanovic
Independent Policy Gradient for Large-Scale Markov Potential Games: Sharper Rates, Function Approximation, and Game-Agnostic Convergence. CoRR (2022)
Jack Umenberger, Max Simchowitz, Juan C. Perdomo, Kaiqing Zhang, Russ Tedrake
Globally Convergent Policy Search for Output Estimation. NeurIPS (2022)
Weichao Mao, Lin Yang, Kaiqing Zhang, Tamer Basar
On Improving Model-Free Algorithms for Decentralized Multi-Agent Reinforcement Learning. ICML (2022)
Sarath Pattathil, Kaiqing Zhang, Asuman E. Ozdaglar
Symmetric (Optimistic) Natural Policy Gradient for Multi-agent Learning with Parameter Convergence. CoRR (2022)
Dongsheng Ding, Chen-Yu Wei, Kaiqing Zhang, Mihailo R. Jovanovic
Independent Policy Gradient for Large-Scale Markov Potential Games: Sharper Rates, Function Approximation, and Game-Agnostic Convergence. ICML (2022)
Asuman E. Ozdaglar, Sarath Pattathil, Jiawei Zhang, Kaiqing Zhang
What is a Good Metric to Study Generalization of Minimax Learners? NeurIPS (2022)
H. J. Terry Suh, Max Simchowitz, Kaiqing Zhang, Russ Tedrake
Do Differentiable Simulators Give Better Policy Gradients? CoRR (2022)
Lirui Wang, Kaiqing Zhang, Yunzhu Li, Yonglong Tian, Russ Tedrake
Does Decentralized Learning with Non-IID Unlabeled Data Benefit from Self Supervision? CoRR (2022)
Jack Umenberger, Max Simchowitz, Juan C. Perdomo, Kaiqing Zhang, Russ Tedrake
Globally Convergent Policy Search over Dynamic Filters for Output Estimation. CoRR (2022)
Yiding Chen, Xuezhou Zhang, Kaiqing Zhang, Mengdi Wang, Xiaojin Zhu
Byzantine-Robust Online and Offline Distributed Reinforcement Learning. CoRR (2022)
Yanli Liu, Kaiqing Zhang, Tamer Basar, Wotao Yin
An Improved Analysis of (Variance-Reduced) Policy Gradient and Natural Policy Gradient Methods. CoRR (2022)
Mingyang Liu, Asuman E. Ozdaglar, Tiancheng Yu, Kaiqing Zhang
The Power of Regularization in Solving Extensive-Form Games. CoRR (2022)
Asuman E. Ozdaglar, Sarath Pattathil, Jiawei Zhang, Kaiqing Zhang
What is a Good Metric to Study Generalization of Minimax Learners? CoRR (2022)
Muhammed O. Sayin, Kaiqing Zhang, Asuman E. Ozdaglar
Fictitious Play in Markov Games with Single Controller. CoRR (2022)
Xingyu Sha, Jiaqi Zhang, Keyou You, Kaiqing Zhang, Tamer Basar
Fully asynchronous policy evaluation in distributed reinforcement learning over networks. Autom. 136 (2022)
Hyung Ju Suh, Max Simchowitz, Kaiqing Zhang, Russ Tedrake
Do Differentiable Simulators Give Better Policy Gradients? ICML (2022)
Tianyi Chen, Kaiqing Zhang, Georgios B. Giannakis, Tamer Basar
Communication-Efficient Policy Gradient Methods for Distributed Reinforcement Learning. IEEE Trans. Control. Netw. Syst. 9 (2) (2022)
Dongsheng Ding, Kaiqing Zhang, Tamer Basar, Mihailo R. Jovanovic
Convergence and optimality of policy gradient primal-dual method for constrained Markov decision processes. ACC (2022)
Constantinos Daskalakis, Noah Golowich, Kaiqing Zhang
The Complexity of Markov Equilibrium in Stochastic Games. CoRR (2022)
Dongsheng Ding, Kaiqing Zhang, Jiali Duan, Tamer Basar, Mihailo R. Jovanovic
Convergence and sample complexity of natural policy gradient primal-dual methods for constrained MDPs. CoRR (2022)
Zengyi Qin, Kaiqing Zhang, Yuxiao Chen, Jingkai Chen, Chuchu Fan
Learning Safe Multi-Agent Control with Decentralized Neural Barrier Certificates. CoRR (2021)
Kaiqing Zhang, Xiangyuan Zhang, Bin Hu, Tamer Basar
Derivative-Free Policy Optimization for Risk-Sensitive and Robust Control Design: Implicit Regularization and Sample Complexity. CoRR (2021)
Zengyi Qin, Kaiqing Zhang, Yuxiao Chen, Jingkai Chen, Chuchu Fan
Learning Safe Multi-agent Control with Decentralized Neural Barrier Certificates. ICLR (2021)
Songtao Lu, Kaiqing Zhang, Tianyi Chen, Tamer Basar, Lior Horesh
Decentralized Policy Gradient Descent Ascent for Safe Multi-Agent Reinforcement Learning. AAAI (2021)
Kaiqing Zhang, Bin Hu, Tamer Basar
Robustness Guarantee: Implicit Regularization and Global Convergence. SIAM J. Control. Optim. 59 (6) (2021)
Kaiqing Zhang, Xiangyuan Zhang, Bin Hu, Tamer Basar
Derivative-Free Policy Optimization for Linear Risk-Sensitive and Robust Control Design: Implicit Regularization and Sample Complexity. NeurIPS (2021)
Wesley Suttle, Kaiqing Zhang, Zhuoran Yang, Ji Liu, David Kraemer
Reinforcement Learning for Cost-Aware Markov Decision Processes. ICML (2021)
Yi Yuan, Kaiqing Zhang, Yiyao Zhang, Jiaqing Yan, Zhijie Wang, Xingran Wang, Mengyang Liu, Xiaoli Li
The Effect of Low-Intensity Transcranial Ultrasound Stimulation on Neural Oscillation and Hemodynamics in the Mouse Visual Cortex Depends on Anesthesia Level and Ultrasound Intensity. IEEE Trans. Biomed. Eng. 68 (5) (2021)
Asuman E. Ozdaglar, Muhammed O. Sayin, Kaiqing Zhang
Independent Learning in Stochastic Games. CoRR (2021)
Kaiqing Zhang, Zhuoran Yang, Tamer Basar
Decentralized multi-agent reinforcement learning with networked agents: recent advances. Frontiers Inf. Technol. Electron. Eng. 22 (6) (2021)
Kaiqing Zhang, Zhuoran Yang, Han Liu, Tong Zhang, Tamer Basar
Finite-Sample Analysis for Decentralized Batch Multiagent Reinforcement Learning With Networked Agents. IEEE Trans. Autom. Control. 66 (12) (2021)
Weichao Mao, Kaiqing Zhang, Ruihao Zhu, David Simchi-Levi, Tamer Basar
Near-Optimal Model-Free Reinforcement Learning in Non-Stationary Episodic MDPs. ICML (2021)
Muhammed O. Sayin, Kaiqing Zhang, David S. Leslie, Tamer Basar, Asuman E. Ozdaglar
Decentralized Q-Learning in Zero-sum Markov Games. CoRR (2021)
Xingran Wang, Yiyao Zhang, Kaiqing Zhang, Yi Yuan
Influence of behavioral state on the neuromodulatory effect of low-intensity transcranial ultrasound stimulation on hippocampal CA1 in mouse. NeuroImage 241 (2021)
Weichao Mao, Tamer Basar, Lin F. Yang, Kaiqing Zhang
Decentralized Cooperative Multi-Agent Reinforcement Learning with Exploration. CoRR (2021)
Muhammed O. Sayin, Kaiqing Zhang, David S. Leslie, Tamer Basar, Asuman E. Ozdaglar
Decentralized Q-learning in Zero-sum Markov Games. NeurIPS (2021)
Kaiqing Zhang, Bin Hu, Tamer Basar
Robustness Guarantee: Implicit Regularization and Global Convergence. L4DC (2020)
Muhammad Aneeq uz Zaman, Kaiqing Zhang, Erik Miehling, Tamer Basar
Reinforcement Learning in Non-Stationary Discrete-Time Linear-Quadratic Mean-Field Games. CDC (2020)
Muhammad Aneeq uz Zaman, Kaiqing Zhang, Erik Miehling, Tamer Basar
Reinforcement Learning in Non-Stationary Discrete-Time Linear-Quadratic Mean-Field Games. CoRR (2020)
Xingyu Sha, Jiaqi Zhang, Kaiqing Zhang, Keyou You, Tamer Basar
Asynchronous Policy Evaluation in Distributed Reinforcement Learning over Networks. CoRR (2020)
Kaiqing Zhang, Yang Liu, Ji Liu, Mingyan Liu, Tamer Basar
Distributed learning of average belief over networks using sequential observations. Autom. 115 (2020)
Kaiqing Zhang, Sham M. Kakade, Tamer Basar, Lin F. Yang
Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample Complexity. CoRR (2020)
Kaiqing Zhang, Tao Sun, Yunzhe Tao, Sahika Genc, Sunil Mallya, Tamer Basar
Robust Multi-Agent Reinforcement Learning with Model Uncertainty. NeurIPS (2020)
Dongsheng Ding, Kaiqing Zhang, Tamer Basar, Mihailo R. Jovanovic
Natural Policy Gradient Primal-Dual Method for Constrained Markov Decision Processes. NeurIPS (2020)
Muhammad Aneeq uz Zaman, Kaiqing Zhang, Erik Miehling, Tamer Basar
Approximate Equilibrium Computation for Discrete-Time Linear-Quadratic Mean-Field Games. CoRR (2020)
Weichao Mao, Kaiqing Zhang, Qiaomin Xie, Tamer Basar
POLY-HOOT: Monte-Carlo Planning in Continuous Space MDPs with Non-Asymptotic Analysis. NeurIPS (2020)
Weichao Mao, Kaiqing Zhang, Erik Miehling, Tamer Basar
Information State Embedding in Partially Observable Cooperative Multi-Agent Reinforcement Learning. CoRR (2020)
Muhammad Aneeq uz Zaman, Kaiqing Zhang, Erik Miehling, Tamer Basar
Approximate Equilibrium Computation for Discrete-Time Linear-Quadratic Mean-Field Games. ACC (2020)
Han Shen, Kaiqing Zhang, Mingyi Hong, Tianyi Chen
Asynchronous Advantage Actor Critic: Non-asymptotic Analysis and Linear Speedup. CoRR (2020)
Weichao Mao, Kaiqing Zhang, Qiaomin Xie, Tamer Basar
POLY-HOOT: Monte-Carlo Planning in Continuous Space MDPs with Non-Asymptotic Analysis. CoRR (2020)
Kaiqing Zhang, Bin Hu, Tamer Basar
On the Stability and Convergence of Robust Adversarial Reinforcement Learning: A Case Study on Linear Quadratic Systems. NeurIPS (2020)
Kaiqing Zhang, Sham M. Kakade, Tamer Basar, Lin F. Yang
Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample Complexity. NeurIPS (2020)
Yanli Liu, Kaiqing Zhang, Tamer Basar, Wotao Yin
An Improved Analysis of (Variance-Reduced) Policy Gradient and Natural Policy Gradient Methods. NeurIPS (2020)
Weichao Mao, Kaiqing Zhang, Ruihao Zhu, David Simchi-Levi, Tamer Basar
Near-Optimal Regret Bounds for Model-Free RL in Non-Stationary Episodic MDPs. CoRR (2020)
Weichao Mao, Kaiqing Zhang, Erik Miehling, Tamer Basar
Information State Embedding in Partially Observable Cooperative Multi-Agent Reinforcement Learning. CDC (2020)
Kaiqing Zhang, Alec Koppel, Hao Zhu, Tamer Basar
Global Convergence of Policy Gradient Methods to (Almost) Locally Optimal Policies. SIAM J. Control. Optim. 58 (6) (2020)
Xiangyuan Zhang, Kaiqing Zhang, Erik Miehling, Tamer Basar
Non-Cooperative Inverse Reinforcement Learning. NeurIPS (2019)
Kaiqing Zhang, Zhuoran Yang, Tamer Basar
Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms. CoRR (2019)
Wesley Suttle, Zhuoran Yang, Kaiqing Zhang, Zhaoran Wang, Tamer Basar, Ji Liu
A Multi-Agent Off-Policy Actor-Critic Algorithm for Distributed Reinforcement Learning. CoRR (2019)
Kaiqing Zhang, Zhuoran Yang, Tamer Basar
Decentralized Multi-Agent Reinforcement Learning with Networked Agents: Recent Advances. CoRR (2019)
Wesley Suttle, Zhuoran Yang, Kaiqing Zhang, Ji Liu
Stochastic Convergence Results for Regularized Actor-Critic Methods. CoRR (2019)
Kaiqing Zhang, Alec Koppel, Hao Zhu, Tamer Basar
Policy Search in Infinite-Horizon Discounted Reinforcement Learning: Advances through Connections to Non-Convex Optimization : Invited Presentation. CISS (2019)
Kaiqing Zhang, Bin Hu, Tamer Basar
Robustness Guarantee: Implicit Regularization and Global Convergence. CoRR (2019)

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Publication Activity (10 Years)

Top Topics

Top Venues

Kaiqing Zhang