Machine learning techniques for spectrum sensing when primary user has multiple transmit powers. - Kaiqing Zhang; Jiachen Li; Feifei Gao (ICCS, 2014)

Enhanced Multi-Parameter Cognitive Architecture for Future Wireless Communications. - Kaiqing Zhang; Feifei Gao; Qihui Wu (CoRR, 2014)

Sequential Detection Aided Modulation Classification in Cognitive Radio Networks. - Lubing Han; Feifei Gao; Kaiqing Zhang; Shun Zhang 003 (GLOBECOM, 2015)

An area state-aided indoor localization algorithm and its implementation. - Kaiqing Zhang; Hong Hu; Wenhan Dai; Yuan Shen 001; Moe Z. Win (ICC Workshops, 2015)

Spectrum prediction and channel selection for sensing-based spectrum sharing scheme using online learning techniques. - Zhao Zhang; Kaiqing Zhang; Feifei Gao; Shun Zhang 003 (PIMRC, 2015)

Enhanced multi-parameter cognitive architecture for future wireless communications. - Feifei Gao; Kaiqing Zhang (IEEE Commun. Mag., 2015)

Indoor Localization Algorithm For Smartphones. - Kaiqing Zhang; Hong Hu; Wenhan Dai; Yuan Shen 001; Moe Z. Win (CoRR, 2015)

On the performance of map-aware cooperative localization. - Kaiqing Zhang; Yuan Shen 001; Moe Z. Win (ICC, 2016)

A game-theoretic approach for communication-free voltage-VAR optimization. - Kaiqing Zhang; Hao Zhu (GlobalSIP, 2017)

Parameter Sensitivity and Dependency Analysis for the WECC Dynamic Composite Load Model. - Kaiqing Zhang; Siming Guo; Hao Zhu (HICSS, 2017)

Consumption Behavior Analytics-Aided Energy Forecasting and Dispatch. - Yingchen Zhang; Rui Yang 015; Kaiqing Zhang; Huaiguang Jiang; Jun Jason Zhang (IEEE Intell. Syst., 2017)

Nonlinear Structured Signal Estimation in High Dimensions via Iterative Hard Thresholding. - Kaiqing Zhang; Zhuoran Yang; Zhaoran Wang 001 (AISTATS, 2018)

Distributed Equilibrium-Learning for Power Network Voltage Control With a Locally Connected Communication Network. - Kaiqing Zhang; Wei Shi 010; Hao Zhu 001; Tamer Basar (ACC, 2018)

A Finite Sample Analysis of the Actor-Critic Algorithm. - Zhuoran Yang; Kaiqing Zhang; Mingyi Hong 001; Tamer Basar (CDC, 2018)

Networked Multi-Agent Reinforcement Learning in Continuous Spaces. - Kaiqing Zhang; Zhuoran Yang; Tamer Basar (CDC, 2018)

Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents. - Kaiqing Zhang; Zhuoran Yang; Han Liu 001; Tong Zhang 001; Tamer Basar (ICML, 2018)

Finite-Sample Analyses for Fully Decentralized Multi-Agent Reinforcement Learning. - Kaiqing Zhang; Zhuoran Yang; Han Liu 001; Tong Zhang 001; Tamer Basar (CoRR, 2018)

Communication-Efficient Distributed Reinforcement Learning. - Tianyi Chen; Kaiqing Zhang; Georgios B. Giannakis; Tamer Basar (CoRR, 2018)

Dynamic Power Distribution System Management With a Locally Connected Communication Network. - Kaiqing Zhang; Wei Shi 010; Hao Zhu 001; Emiliano Dall'Anese; Tamer Basar (IEEE J. Sel. Top. Signal Process., 2018)

Online Planning for Decentralized Stochastic Control with Partial History Sharing. - Kaiqing Zhang; Erik Miehling; Tamer Basar (ACC, 2019)

A Communication-Efficient Multi-Agent Actor-Critic Algorithm for Distributed Reinforcement Learning. - Yixuan Lin; Kaiqing Zhang; Zhuoran Yang; Zhaoran Wang 001; Tamer Basar; Romeil Sandhu; Ji Liu 001 (CDC, 2019)

Convergence and Iteration Complexity of Policy Gradient Method for Infinite-horizon Reinforcement Learning. - Kaiqing Zhang; Alec Koppel; Hao Zhu 001; Tamer Basar (CDC, 2019)

Policy Search in Infinite-Horizon Discounted Reinforcement Learning: Advances through Connections to Non-Convex Optimization : Invited Presentation. - Kaiqing Zhang; Alec Koppel; Hao Zhu 001; Tamer Basar (CISS, 2019)

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

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

A Multi-Agent Off-Policy Actor-Critic Algorithm for Distributed Reinforcement Learning. - Wesley Suttle; Zhuoran Yang; Kaiqing Zhang; Zhaoran Wang 001; Tamer Basar; Ji Liu 001 (CoRR, 2019)

Stochastic Convergence Results for Regularized Actor-Critic Methods. - Wesley Suttle; Zhuoran Yang; Kaiqing Zhang; Ji Liu 001 (CoRR, 2019)

Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms. - Kaiqing Zhang; Zhuoran Yang; Tamer Basar (CoRR, 2019)

Projected Stochastic Primal-Dual Method for Constrained Online Learning With Kernels. - Alec Koppel; Kaiqing Zhang; Hao Zhu 001; Tamer Basar (IEEE Trans. Signal Process., 2019)

Approximate Equilibrium Computation for Discrete-Time Linear-Quadratic Mean-Field Games. - Muhammad Aneeq uz Zaman; Kaiqing Zhang; Erik Miehling; Tamer Basar (ACC, 2020)

Information State Embedding in Partially Observable Cooperative Multi-Agent Reinforcement Learning. - Weichao Mao; Kaiqing Zhang; Erik Miehling; Tamer Basar (CDC, 2020)

Reinforcement Learning in Non-Stationary Discrete-Time Linear-Quadratic Mean-Field Games. - Muhammad Aneeq uz Zaman; Kaiqing Zhang; Erik Miehling; Tamer Basar (CDC, 2020)

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

An Improved Analysis of (Variance-Reduced) Policy Gradient and Natural Policy Gradient Methods. - Yanli Liu 003; Kaiqing Zhang; Tamer Basar; Wotao Yin (NeurIPS, 2020)

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

On the Stability and Convergence of Robust Adversarial Reinforcement Learning: A Case Study on Linear Quadratic Systems. - Kaiqing Zhang; Bin Hu 002; Tamer Basar (NeurIPS, 2020)

Robust Multi-Agent Reinforcement Learning with Model Uncertainty. - Kaiqing Zhang; Tao Sun 008; Yunzhe Tao; Sahika Genc; Sunil Mallya; Tamer Basar (NeurIPS, 2020)

Distributed learning of average belief over networks using sequential observations. - Kaiqing Zhang; Yang Liu 018; Ji Liu 001; Mingyan Liu; Tamer Basar (Autom., 2020)

Asynchronous Policy Evaluation in Distributed Reinforcement Learning over Networks. - Xingyu Sha; Jiaqi Zhang 001; Kaiqing Zhang; Keyou You; Tamer Basar (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 Advantage Actor Critic: Non-asymptotic Analysis and Linear Speedup. - Han Shen; Kaiqing Zhang; Mingyi Hong 001; Tianyi Chen (CoRR, 2020)

Global Convergence of Policy Gradient Methods to (Almost) Locally Optimal Policies. - Kaiqing Zhang; Alec Koppel; Hao Zhu 001; Tamer Basar (SIAM J. Control. Optim., 2020)

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

Learning Safe Multi-agent Control with Decentralized Neural Barrier Certificates. - Zengyi Qin; Kaiqing Zhang; Yuxiao Chen 001; Jingkai Chen; Chuchu Fan (ICLR, 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 001; David N. Kraemer (ICML, 2021)

Decentralized Q-learning in Zero-sum Markov Games. - Muhammed O. Sayin; Kaiqing Zhang; David S. Leslie; Tamer Basar; Asuman E. 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 002; Tamer Basar (NeurIPS, 2021)

Derivative-Free Policy Optimization for Risk-Sensitive and Robust Control Design: Implicit Regularization and Sample Complexity. - Kaiqing Zhang; Xiangyuan Zhang; Bin Hu 002; Tamer Basar (CoRR, 2021)

Decentralized Cooperative Multi-Agent Reinforcement Learning with Exploration. - Weichao Mao; Tamer Basar; Lin F. Yang; Kaiqing Zhang (CoRR, 2021)

Independent Learning in Stochastic Games. - Asuman E. Ozdaglar; Muhammed O. Sayin; Kaiqing Zhang (CoRR, 2021)

Decentralized multi-agent reinforcement learning with networked agents: recent advances. - Kaiqing Zhang; Zhuoran Yang; Tamer Basar (Frontiers Inf. Technol. Electron. Eng., 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 004 (NeuroImage, 2021)

Policy Optimization for ℋ2 Linear Control with ℋ∞ Robustness Guarantee: Implicit Regularization and Global Convergence. - Kaiqing Zhang; Bin Hu 002; Tamer Basar (SIAM J. Control. Optim., 2021)

Finite-Sample Analysis for Decentralized Batch Multiagent Reinforcement Learning With Networked Agents. - Kaiqing Zhang; Zhuoran Yang; Han Liu 001; Tong Zhang 001; Tamer Basar (IEEE Trans. Autom. Control., 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 004; Kaiqing Zhang; Yiyao Zhang; Jiaqing Yan; Zhijie Wang 011; Xingran Wang; Mengyang Liu; Xiaoli Li 002 (IEEE Trans. Biomed. Eng., 2021)

Reinforcement learning for multi-agent and robust control systems - Kaiqing Zhang (2021)

Convergence and optimality of policy gradient primal-dual method for constrained Markov decision processes. - Dongsheng Ding; Kaiqing Zhang; Tamer Basar; Mihailo R. Jovanovic (ACC, 2022)

Discrete Approximate Information States in Partially Observable Environments. - Lujie Yang; Kaiqing Zhang; Alexandre Amice; Yunzhu Li; Russ Tedrake (ACC, 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 (ICML, 2022)

On Improving Model-Free Algorithms for Decentralized Multi-Agent Reinforcement Learning. - Weichao Mao; Lin Yang 011; Kaiqing Zhang; Tamer Basar (ICML, 2022)

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

What is a Good Metric to Study Generalization of Minimax Learners? - Asuman E. Ozdaglar; Sarath Pattathil; Jiawei Zhang 007; Kaiqing Zhang (NeurIPS, 2022)

Globally Convergent Policy Search for Output Estimation. - Jack Umenberger; Max Simchowitz; Juan C. Perdomo; Kaiqing Zhang; Russ Tedrake (NeurIPS, 2022)

Fictitious Play in Markov Games with Single Controller. - Muhammed O. Sayin; Kaiqing Zhang; Asuman E. Ozdaglar (EC, 2022)

Fully asynchronous policy evaluation in distributed reinforcement learning over networks. - Xingyu Sha; Jiaqi Zhang 001; Keyou You; Kaiqing Zhang; Tamer Basar (Autom., 2022)

Globally Convergent Policy Search over Dynamic Filters for Output Estimation. - Jack Umenberger; Max Simchowitz; Juan C. Perdomo; Kaiqing Zhang; Russ Tedrake (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)

Towards a Theoretical Foundation of Policy Optimization for Learning Control Policies. - Bin Hu 002; Kaiqing Zhang; Na Li 002; Mehran Mesbahi; Maryam Fazel; Tamer Basar (CoRR, 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)

Communication-Efficient Policy Gradient Methods for Distributed Reinforcement Learning. - Tianyi Chen; Kaiqing Zhang; Georgios B. Giannakis; Tamer Basar (IEEE Trans. Control. Netw. Syst., 2022)

Byzantine-Robust Online and Offline Distributed Reinforcement Learning. - Yiding Chen; Xuezhou Zhang; Kaiqing Zhang; Mengdi Wang; Xiaojin Zhu 001 (AISTATS, 2023)

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

Toward Understanding State Representation Learning in MuZero: A Case Study in Linear Quadratic Gaussian Control. - Yi Tian; Kaiqing Zhang; Russ Tedrake; Suvrit Sra (CDC, 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 (COLT, 2023)

The Complexity of Markov Equilibrium in Stochastic Games. - Constantinos Daskalakis; Noah Golowich; Kaiqing Zhang (COLT, 2023)

Tackling Combinatorial Distribution Shift: A Matrix Completion Perspective. - Max Simchowitz; Abhishek Gupta 004; Kaiqing Zhang (COLT, 2023)

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

Learning to Extrapolate: A Transductive Approach. - Aviv Netanyahu; Abhishek Gupta 004; Max Simchowitz; Kaiqing Zhang; Pulkit Agrawal 001 (ICLR, 2023)

Does Learning from Decentralized Non-IID Unlabeled Data Benefit from Self Supervision? - Lirui Wang; Kaiqing Zhang; Yunzhu Li; Yonglong Tian; Russ Tedrake (ICLR, 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 007; Kaiqing Zhang (ICML, 2023)

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

Self-Supervised Reinforcement Learning that Transfers using Random Features. - Boyuan Chen 003; Chuning Zhu; Pulkit Agrawal 001; Kaiqing Zhang; Abhishek Gupta 004 (NeurIPS, 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 (NeurIPS, 2023)

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

Multi-Player Zero-Sum Markov Games with Networked Separable Interactions. - Chanwoo Park; Kaiqing Zhang; Asuman E. Ozdaglar (NeurIPS, 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)

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)

Towards Understanding Asynchronous Advantage Actor-Critic: Convergence and Linear Speedup. - Han Shen; Kaiqing Zhang; Mingyi Hong 001; Tianyi Chen (IEEE Trans. Signal Process., 2023)

Toward a Theoretical Foundation of Policy Optimization for Learning Control Policies. - Bin Hu 002; Kaiqing Zhang; Na Li 002; Mehran Mesbahi; Maryam Fazel; Tamer Basar (Annu. Rev. Control. Robotics Auton. Syst., 2023)

Robot Fleet Learning via Policy Merging. - Lirui Wang; Kaiqing Zhang; Allan Zhou; Max Simchowitz; Russ Tedrake (ICLR, 2024)

Provable Partially Observable Reinforcement Learning with Privileged Information. - Yang Cai 001; Xiangyu Liu; Argyris Oikonomou; Kaiqing Zhang (NeurIPS, 2024)

Two-Timescale Q-Learning with Function Approximation in Zero-Sum Stochastic Games. - Zaiwei Chen; Kaiqing Zhang; Eric Mazumdar; Asuman E. Ozdaglar; Adam Wierman (EC, 2024)

RLHF from Heterogeneous Feedback via Personalization and Preference Aggregation. - Chanwoo Park; Mingyang Liu; Dingwen Kong; Kaiqing Zhang; Asuman E. Ozdaglar (CoRR, 2024)

Last-Iterate Convergence of Payoff-Based Independent Learning in Zero-Sum Stochastic Games. - Zaiwei Chen; Kaiqing Zhang; Eric Mazumdar; Asuman E. Ozdaglar; Adam Wierman (CoRR, 2024)

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

MAPoRL: Multi-Agent Post-Co-Training for Collaborative Large Language Models with Reinforcement Learning. - Chanwoo Park; Seungju Han 002; Xingzhi Guo; Asuman E. Ozdaglar; Kaiqing Zhang; Joo-Kyung Kim (ACL (1), 2025)

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

Model-Free Nonstationary Reinforcement Learning: Near-Optimal Regret and Applications in Multiagent Reinforcement Learning and Inventory Control. - Weichao Mao; Kaiqing Zhang; Ruihao Zhu; David Simchi-Levi; Tamer Basar (Manag. Sci., 2025)