Kaiqing Zhang

According to our database, Kaiqing Zhang authored at least 95 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Do LLM Agents Have Regret? A Case Study in Online Learning and Games.

Chanwoo Park, Xiangyu Liu, Asuman E. Ozdaglar, Kaiqing Zhang

CoRR, 2024

2023

Toward a Theoretical Foundation of Policy Optimization for Learning Control Policies.

Bin Hu, Kaiqing Zhang, Na Li, Mehran Mesbahi, Maryam Fazel, Tamer Basar

Annu. Rev. Control. Robotics Auton. Syst., May, 2023

Towards Understanding Asynchronous Advantage Actor-Critic: Convergence and Linear Speedup.

Han Shen, Kaiqing Zhang, Mingyi Hong, Tianyi Chen

IEEE Trans. Signal Process., 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

J. Mach. Learn. Res., 2023

Two-Timescale Q-Learning with Function Approximation in Zero-Sum Stochastic Games.

Zaiwei Chen, Kaiqing Zhang, Eric Mazumdar, Asuman E. Ozdaglar, Adam Wierman

CoRR, 2023

Fleet Policy Learning via Weight Merging and An Application to Robotic Tool-Use.

Lirui Wang, Kaiqing Zhang, Allan Zhou, Max Simchowitz, Russ Tedrake

CoRR, 2023

Self-Supervised Reinforcement Learning that Transfers using Random Features.

Boyuan Chen, Chuning Zhu, Pulkit Agrawal, Kaiqing Zhang, Abhishek Gupta

CoRR, 2023

Multi-Player Zero-Sum Markov Games with Networked Separable Interactions.

Chanwoo Park, Kaiqing Zhang, Asuman E. Ozdaglar

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Last-Iterate Convergent Policy Gradient Primal-Dual Methods for Constrained MDPs.

Dongsheng Ding, Chen-Yu Wei, Kaiqing Zhang, Alejandro Ribeiro

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Finite-Sample Analysis of Payoff-Based Independent Learning in Zero-Sum Stochastic Games.

Zaiwei Chen, Kaiqing Zhang, Eric Mazumdar, Asuman E. Ozdaglar, Adam Wierman

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Self-Supervised Reinforcement Learning that Transfers using Random Features.

Boyuan Chen, Chuning Zhu, Pulkit Agrawal, Kaiqing Zhang, Abhishek Gupta

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Can Direct Latent Model Learning Solve Linear Quadratic Gaussian Control?

Yi Tian, Kaiqing Zhang, Russ Tedrake, Suvrit Sra

Proceedings of the Learning for Dynamics and Control Conference, 2023

Revisiting the Linear-Programming Framework for Offline RL with General Function Approximation.

Asuman E. Ozdaglar, Sarath Pattathil, Jiawei Zhang, Kaiqing Zhang

Proceedings of the International Conference on Machine Learning, 2023

Partially Observable Multi-agent RL with (Quasi-)Efficiency: The Blessing of Information Sharing.

Xiangyu Liu, Kaiqing Zhang

Proceedings of the International Conference on Machine Learning, 2023

Does Learning from Decentralized Non-IID Unlabeled Data Benefit from Self Supervision?

Lirui Wang, Kaiqing Zhang, Yunzhu Li, Yonglong Tian, Russ Tedrake

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Learning to Extrapolate: A Transductive Approach.

Aviv Netanyahu, Abhishek Gupta, Max Simchowitz, Kaiqing Zhang, Pulkit Agrawal

Proceedings of the Eleventh International Conference on Learning Representations, 2023

The Power of Regularization in Solving Extensive-Form Games.

Mingyang Liu, Asuman E. Ozdaglar, Tiancheng Yu, Kaiqing Zhang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Tackling Combinatorial Distribution Shift: A Matrix Completion Perspective.

Max Simchowitz, Abhishek Gupta, Kaiqing Zhang

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

The Complexity of Markov Equilibrium in Stochastic Games.

Constantinos Daskalakis, Noah Golowich, Kaiqing Zhang

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 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 S. Du

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

Toward Understanding State Representation Learning in MuZero: A Case Study in Linear Quadratic Gaussian Control.

Yi Tian, Kaiqing Zhang, Russ Tedrake, Suvrit Sra

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

Symmetric (Optimistic) Natural Policy Gradient for Multi-Agent Learning with Parameter Convergence.

Sarath Pattathil, Kaiqing Zhang, Asuman E. Ozdaglar

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Byzantine-Robust Online and Offline Distributed Reinforcement Learning.

Yiding Chen, Xuezhou Zhang, Kaiqing Zhang, Mengdi Wang, Xiaojin Zhu

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Communication-Efficient Policy Gradient Methods for Distributed Reinforcement Learning.

Tianyi Chen, Kaiqing Zhang, Georgios B. Giannakis, Tamer Basar

IEEE Trans. Control. Netw. Syst., 2022

Does Decentralized Learning with Non-IID Unlabeled Data Benefit from Self Supervision?

Lirui Wang, Kaiqing Zhang, Yunzhu Li, Yonglong Tian, Russ Tedrake

CoRR, 2022

Towards a Theoretical Foundation of Policy Optimization for Learning Control Policies.

Bin Hu, Kaiqing Zhang, Na Li, Mehran Mesbahi, Maryam Fazel, Tamer Basar

CoRR, 2022

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

CoRR, 2022

Globally Convergent Policy Search over Dynamic Filters for Output Estimation.

Jack Umenberger, Max Simchowitz, Juan C. Perdomo, Kaiqing Zhang, Russ Tedrake

CoRR, 2022

Do Differentiable Simulators Give Better Policy Gradients?

H. J. Terry Suh, Max Simchowitz, Kaiqing Zhang, Russ Tedrake

CoRR, 2022

Fully asynchronous policy evaluation in distributed reinforcement learning over networks.

Xingyu Sha, Jiaqi Zhang, Keyou You, Kaiqing Zhang, Tamer Basar

Autom., 2022

Fictitious Play in Markov Games with Single Controller.

Muhammed O. Sayin, Kaiqing Zhang, Asuman E. Ozdaglar

Proceedings of the EC '22: The 23rd ACM Conference on Economics and Computation, Boulder, CO, USA, July 11, 2022

Globally Convergent Policy Search for Output Estimation.

Jack Umenberger, Max Simchowitz, Juan C. Perdomo, Kaiqing Zhang, Russ Tedrake

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

What is a Good Metric to Study Generalization of Minimax Learners?

Asuman E. Ozdaglar, Sarath Pattathil, Jiawei Zhang, Kaiqing Zhang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Do Differentiable Simulators Give Better Policy Gradients?

Hyung Ju Suh, Max Simchowitz, Kaiqing Zhang, Russ Tedrake

Proceedings of the International Conference on Machine Learning, 2022

On Improving Model-Free Algorithms for Decentralized Multi-Agent Reinforcement Learning.

Weichao Mao, Lin Yang, Kaiqing Zhang, Tamer Basar

Proceedings of the International Conference on Machine Learning, 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 R. Jovanovic

Proceedings of the International Conference on Machine Learning, 2022

Discrete Approximate Information States in Partially Observable Environments.

Lujie Yang, Kaiqing Zhang, Alexandre Amice, Yunzhu Li, Russ Tedrake

Proceedings of the American Control Conference, 2022

Convergence and optimality of policy gradient primal-dual method for constrained Markov decision processes.

Dongsheng Ding, Kaiqing Zhang, Tamer Basar, Mihailo R. Jovanovic

Proceedings of the American Control Conference, 2022

2021

Reinforcement learning for multi-agent and robust control systems

Kaiqing Zhang

PhD thesis, 2021

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.

Yi Yuan, Kaiqing Zhang, Yiyao Zhang, Jiaqing Yan, Zhijie Wang, Xingran Wang, Mengyang Liu, Xiaoli Li

IEEE Trans. Biomed. Eng., 2021

Finite-Sample Analysis for Decentralized Batch Multiagent Reinforcement Learning With Networked Agents.

Kaiqing Zhang, Zhuoran Yang, Han Liu, Tong Zhang, Tamer Basar

IEEE Trans. Autom. Control., 2021

Policy Optimization for ℋ₂ Linear Control with ℋ_∞ Robustness Guarantee: Implicit Regularization and Global Convergence.

Kaiqing Zhang, Bin Hu, Tamer Basar

SIAM J. Control. Optim., 2021

Influence of behavioral state on the neuromodulatory effect of low-intensity transcranial ultrasound stimulation on hippocampal CA1 in mouse.

Xingran Wang, Yiyao Zhang, Kaiqing Zhang, Yi Yuan

NeuroImage, 2021

Decentralized multi-agent reinforcement learning with networked agents: recent advances.

Kaiqing Zhang, Zhuoran Yang, Tamer Basar

Frontiers Inf. Technol. Electron. Eng., 2021

Independent Learning in Stochastic Games.

Asuman E. Ozdaglar, Muhammed O. Sayin, Kaiqing Zhang

CoRR, 2021

Decentralized Cooperative Multi-Agent Reinforcement Learning with Exploration.

Weichao Mao, Tamer Basar, Lin F. Yang, Kaiqing Zhang

CoRR, 2021

Derivative-Free Policy Optimization for Risk-Sensitive and Robust Control Design: Implicit Regularization and Sample Complexity.

Kaiqing Zhang, Xiangyuan Zhang, Bin Hu, Tamer Basar

CoRR, 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

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Decentralized Q-learning in Zero-sum Markov Games.

Muhammed O. Sayin, Kaiqing Zhang, David S. Leslie, Tamer Basar, Asuman E. Ozdaglar

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Reinforcement Learning for Cost-Aware Markov Decision Processes.

Wesley Suttle, Kaiqing Zhang, Zhuoran Yang, Ji Liu, David N. Kraemer

Proceedings of the 38th International Conference on Machine Learning, 2021

Near-Optimal Model-Free Reinforcement Learning in Non-Stationary Episodic MDPs.

Weichao Mao, Kaiqing Zhang, Ruihao Zhu, David Simchi-Levi, Tamer Basar

Proceedings of the 38th International Conference on Machine Learning, 2021

Learning Safe Multi-agent Control with Decentralized Neural Barrier Certificates.

Zengyi Qin, Kaiqing Zhang, Yuxiao Chen, Jingkai Chen, Chuchu Fan

Proceedings of the 9th International Conference on Learning Representations, 2021

Decentralized Policy Gradient Descent Ascent for Safe Multi-Agent Reinforcement Learning.

Songtao Lu, Kaiqing Zhang, Tianyi Chen, Tamer Basar, Lior Horesh

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Global Convergence of Policy Gradient Methods to (Almost) Locally Optimal Policies.

Kaiqing Zhang, Alec Koppel, Hao Zhu, Tamer Basar

SIAM J. Control. Optim., 2020

Asynchronous Advantage Actor Critic: Non-asymptotic Analysis and Linear Speedup.

Han Shen, Kaiqing Zhang, Mingyi Hong, Tianyi Chen

CoRR, 2020

Near-Optimal Regret Bounds for Model-Free RL in Non-Stationary Episodic MDPs.

Weichao Mao, Kaiqing Zhang, Ruihao Zhu, David Simchi-Levi, Tamer Basar

CoRR, 2020

Asynchronous Policy Evaluation in Distributed Reinforcement Learning over Networks.

Xingyu Sha, Jiaqi Zhang, Kaiqing Zhang, Keyou You, Tamer Basar

CoRR, 2020

Distributed learning of average belief over networks using sequential observations.

Kaiqing Zhang, Yang Liu, Ji Liu, Mingyan Liu, Tamer Basar

Autom., 2020

Robust Multi-Agent Reinforcement Learning with Model Uncertainty.

Kaiqing Zhang, Tao Sun, Yunzhe Tao, Sahika Genc, Sunil Mallya, Tamer Basar

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

On the Stability and Convergence of Robust Adversarial Reinforcement Learning: A Case Study on Linear Quadratic Systems.

Kaiqing Zhang, Bin Hu, Tamer Basar

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

POLY-HOOT: Monte-Carlo Planning in Continuous Space MDPs with Non-Asymptotic Analysis.

Weichao Mao, Kaiqing Zhang, Qiaomin Xie, Tamer Basar

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

An Improved Analysis of (Variance-Reduced) Policy Gradient and Natural Policy Gradient Methods.

Yanli Liu, Kaiqing Zhang, Tamer Basar, Wotao Yin

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Natural Policy Gradient Primal-Dual Method for Constrained Markov Decision Processes.

Dongsheng Ding, Kaiqing Zhang, Tamer Basar, Mihailo R. Jovanovic

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Reinforcement Learning in Non-Stationary Discrete-Time Linear-Quadratic Mean-Field Games.

Muhammad Aneeq uz Zaman, Kaiqing Zhang, Erik Miehling, Tamer Basar

Proceedings of the 59th IEEE Conference on Decision and Control, 2020

Information State Embedding in Partially Observable Cooperative Multi-Agent Reinforcement Learning.

Weichao Mao, Kaiqing Zhang, Erik Miehling, Tamer Basar

Proceedings of the 59th IEEE Conference on Decision and Control, 2020

Approximate Equilibrium Computation for Discrete-Time Linear-Quadratic Mean-Field Games.

Muhammad Aneeq uz Zaman, Kaiqing Zhang, Erik Miehling, Tamer Basar

Proceedings of the 2020 American Control Conference, 2020

2019

Projected Stochastic Primal-Dual Method for Constrained Online Learning With Kernels.

Alec Koppel, Kaiqing Zhang, Hao Zhu, Tamer Basar

IEEE Trans. Signal Process., 2019

Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms.

Kaiqing Zhang, Zhuoran Yang, Tamer Basar

CoRR, 2019

Stochastic Convergence Results for Regularized Actor-Critic Methods.

Wesley Suttle, Zhuoran Yang, Kaiqing Zhang, Ji Liu

CoRR, 2019

A Multi-Agent Off-Policy Actor-Critic Algorithm for Distributed Reinforcement Learning.

Wesley Suttle, Zhuoran Yang, Kaiqing Zhang, Zhaoran Wang, Tamer Basar, Ji Liu

CoRR, 2019

Non-Cooperative Inverse Reinforcement Learning.

Xiangyuan Zhang, Kaiqing Zhang, Erik Miehling, Tamer Basar

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Policy Optimization Provably Converges to Nash Equilibria in Zero-Sum Linear Quadratic Games.

Kaiqing Zhang, Zhuoran Yang, Tamer Basar

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Policy Search in Infinite-Horizon Discounted Reinforcement Learning: Advances through Connections to Non-Convex Optimization : Invited Presentation.

Kaiqing Zhang, Alec Koppel, Hao Zhu, Tamer Basar

Proceedings of the 53rd Annual Conference on Information Sciences and Systems, 2019

Convergence and Iteration Complexity of Policy Gradient Method for Infinite-horizon Reinforcement Learning.

Kaiqing Zhang, Alec Koppel, Hao Zhu, Tamer Basar

Proceedings of the 58th IEEE Conference on Decision and Control, 2019

A Communication-Efficient Multi-Agent Actor-Critic Algorithm for Distributed Reinforcement Learning.

Yixuan Lin, Kaiqing Zhang, Zhuoran Yang, Zhaoran Wang, Tamer Basar, Romeil Sandhu, Ji Liu

Proceedings of the 58th IEEE Conference on Decision and Control, 2019

Online Planning for Decentralized Stochastic Control with Partial History Sharing.

Kaiqing Zhang, Erik Miehling, Tamer Basar

Proceedings of the 2019 American Control Conference, 2019

2018

Dynamic Power Distribution System Management With a Locally Connected Communication Network.

Kaiqing Zhang, Wei Shi, Hao Zhu, Emiliano Dall'Anese, Tamer Basar

IEEE J. Sel. Top. Signal Process., 2018

Communication-Efficient Distributed Reinforcement Learning.

Tianyi Chen, Kaiqing Zhang, Georgios B. Giannakis, Tamer Basar

CoRR, 2018

Finite-Sample Analyses for Fully Decentralized Multi-Agent Reinforcement Learning.

Kaiqing Zhang, Zhuoran Yang, Han Liu, Tong Zhang, Tamer Basar

CoRR, 2018

Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents.

Kaiqing Zhang, Zhuoran Yang, Han Liu, Tong Zhang, Tamer Basar

Proceedings of the 35th International Conference on Machine Learning, 2018

Networked Multi-Agent Reinforcement Learning in Continuous Spaces.

Kaiqing Zhang, Zhuoran Yang, Tamer Basar

Proceedings of the 57th IEEE Conference on Decision and Control, 2018

A Finite Sample Analysis of the Actor-Critic Algorithm.

Zhuoran Yang, Kaiqing Zhang, Mingyi Hong, Tamer Basar

Proceedings of the 57th IEEE Conference on Decision and Control, 2018

Distributed Equilibrium-Learning for Power Network Voltage Control With a Locally Connected Communication Network.

Kaiqing Zhang, Wei Shi, Hao Zhu, Tamer Basar

Proceedings of the 2018 Annual American Control Conference, 2018

Nonlinear Structured Signal Estimation in High Dimensions via Iterative Hard Thresholding.

Kaiqing Zhang, Zhuoran Yang, Zhaoran Wang

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Consumption Behavior Analytics-Aided Energy Forecasting and Dispatch.

Yingchen Zhang, Rui Yang, Kaiqing Zhang, Huaiguang Jiang, Jun Jason Zhang

IEEE Intell. Syst., 2017

Parameter Sensitivity and Dependency Analysis for the WECC Dynamic Composite Load Model.

Kaiqing Zhang, Siming Guo, Hao Zhu

Proceedings of the 50th Hawaii International Conference on System Sciences, 2017

A game-theoretic approach for communication-free voltage-VAR optimization.

Kaiqing Zhang, Hao Zhu

Proceedings of the 2017 IEEE Global Conference on Signal and Information Processing, 2017

2016

On the performance of map-aware cooperative localization.

Kaiqing Zhang, Yuan Shen, Moe Z. Win

Proceedings of the 2016 IEEE International Conference on Communications, 2016

2015

Indoor Localization Algorithm For Smartphones.

Kaiqing Zhang, Hong Hu, Wenhan Dai, Yuan Shen, Moe Z. Win

CoRR, 2015

Enhanced multi-parameter cognitive architecture for future wireless communications.

Feifei Gao, Kaiqing Zhang

IEEE Commun. Mag., 2015

Spectrum prediction and channel selection for sensing-based spectrum sharing scheme using online learning techniques.

Zhao Zhang, Kaiqing Zhang, Feifei Gao, Shun Zhang

Proceedings of the 26th IEEE Annual International Symposium on Personal, 2015

An area state-aided indoor localization algorithm and its implementation.

Kaiqing Zhang, Hong Hu, Wenhan Dai, Yuan Shen, Moe Z. Win

Proceedings of the IEEE International Conference on Communication, 2015

Sequential Detection Aided Modulation Classification in Cognitive Radio Networks.

Lubing Han, Feifei Gao, Kaiqing Zhang, Shun Zhang

Proceedings of the 2015 IEEE Global Communications Conference, 2015

2014

Enhanced Multi-Parameter Cognitive Architecture for Future Wireless Communications.

Kaiqing Zhang, Feifei Gao, Qihui Wu

CoRR, 2014

Machine learning techniques for spectrum sensing when primary user has multiple transmit powers.

Kaiqing Zhang, Jiachen Li, Feifei Gao

Proceedings of the IEEE International Conference on Communication Systems, 2014