Kaiqing Zhang

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Tamer BaşarSwanlund Endowed Chair Emeritus & CAS Professor Emeritus of ECE, University of IllinoisAdresse e-mail validée de illinois.edu
Zhuoran YangYale UniversityAdresse e-mail validée de yale.edu
Asuman OzdaglarMathworks Professor, EECS, MITAdresse e-mail validée de mit.edu
Hao ZhuAssociate Professor of ECEAdresse e-mail validée de utexas.edu
Russ TedrakeMIT (EECS, MechE, Aero/Astro) and Toyota Research InstituteAdresse e-mail validée de mit.edu
Max SimchowitzMITAdresse e-mail validée de andrew.cmu.edu
Tong ZhangUIUCAdresse e-mail validée de tongzhang-ml.org
Mihailo JovanovicUniversity of Southern CaliforniaAdresse e-mail validée de usc.edu
Lin F. Yang (杨林)Assistant Professor, Department of Electrical and Computer Engineering @ UCLAAdresse e-mail validée de ee.ucla.edu
H.J. Terry SuhMassachusetts Institute of TechnologyAdresse e-mail validée de mit.edu
Chen-Yu WeiAssistant Professor, University of VirginiaAdresse e-mail validée de virginia.edu
Abhishek GuptaUniversity of WashingtonAdresse e-mail validée de cs.washington.edu
Sham M KakadeHarvard UniversityAdresse e-mail validée de seas.harvard.edu
Chuchu FanAssociate Professor of Aeronautics and Astronautics at MITAdresse e-mail validée de mit.edu
Wotao YinDAMO Academy, Alibaba Group USAdresse e-mail validée de alibaba-inc.com
Maryam FazelMoorthy Family Professor of Electrical and Computer Engineering, University of WashingtonAdresse e-mail validée de uw.edu
Na LiWinokur Family Professor of Electrical Engineering and Applied Mathematics, HarvardAdresse e-mail validée de seas.harvard.edu
Wei (Wilbur) ShiPostdoctoral Research Associate, Princeton UniversityAdresse e-mail validée de princeton.edu
Noah GolowichMITAdresse e-mail validée de mit.edu
Constantinos DaskalakisProfessor of Computer Science, MITAdresse e-mail validée de csail.mit.edu

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Kaiqing Zhang

Assistant Professor, University of Maryland, College Park

Adresse e-mail validée de umd.edu - Page d'accueil

Systems and Control Machine Learning Game Theory Control Theory Robotics


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Multi-agent reinforcement learning: A selective overview of theories and algorithms K Zhang, Z Yang, T Başar Studies in Systems, Decision and Control, Handbook on RL and Control, 2021	1827	2021
Fully decentralized multi-agent reinforcement learning with networked agents K Zhang, Z Yang, H Liu, T Zhang, T Başar International Conference on Machine Learning (ICML), 2018	756	2018
Global convergence of policy gradient methods to (almost) locally optimal policies K Zhang, A Koppel, H Zhu, T Başar SIAM Journal on Control and Optimization (SICON), 2019	251*	2019
Convergence and sample complexity of natural policy gradient primal-dual methods for constrained MDPs D Ding, K Zhang, J Duan, T Başar, MR Jovanović arXiv preprint arXiv:2206.02346, 2022	235*	2022
Policy optimization for linear control with robustness guarantee: Implicit regularization and global convergence K Zhang, B Hu, T Başar SIAM Journal on Control and Optimization (SICON), 2021	180*	2021
Model-based multi-agent RL in zero-sum Markov games with near-optimal sample complexity K Zhang, SM Kakade, T Basar, LF Yang Journal of Machine Learning Research 24 (175), 1-53, 2023	162	2023
Learning safe multi-agent control with decentralized neural barrier certificates Z Qin, K Zhang, Y Chen, J Chen, C Fan International Conference on Learning Representations (ICLR), 2021	161	2021
Policy optimization provably converges to Nash equilibria in zero-sum linear quadratic games K Zhang, Z Yang, T Basar Advances in Neural Information Processing Systems, 11602-11614, 2019	151	2019
Communication-efficient policy gradient methods for distributed reinforcement learning T Chen, K Zhang, GB Giannakis, T Başar IEEE Transactions on Control of Network Systems, 2018	133*	2018
An improved analysis of (variance-reduced) policy gradient and natural policy gradient methods Y Liu, K Zhang, T Basar, W Yin Advances in Neural Information Processing Systems 33, 2020	124	2020
Networked multi-agent reinforcement learning in continuous spaces K Zhang, Z Yang, T Basar 2018 IEEE Conference on Decision and Control (CDC), 2771-2776, 2018	122	2018
Do differentiable simulators give better policy gradients? HJ Suh, M Simchowitz, K Zhang, R Tedrake International Conference on Machine Learning 162, 20668-20696, 2022	121	2022
Decentralized Q-Learning in zero-sum Markov games MO Sayin, K Zhang, DS Leslie, T Basar, A Ozdaglar Advances in Neural Information Processing Systems 34, 2021	117	2021
A multi-agent off-policy actor-critic algorithm for distributed reinforcement learning W Suttle, Z Yang, K Zhang, Z Wang, T Başar, J Liu IFAC-PapersOnLine 53 (2), 1549-1554, 2020	117*	2020
Dependency analysis and improved parameter estimation for dynamic composite load modeling K Zhang, H Zhu, S Guo IEEE Transactions on Power Systems 32 (4), 3287-3297, 2016	115	2016
Robust multi-agent reinforcement learning with model uncertainty K Zhang, T Sun, Y Tao, S Genc, S Mallya, T Basar Advances in Neural Information Processing Systems 33, 2020	110	2020
Finite-sample analysis for decentralized batch multi-agent reinforcement learning with networked agents K Zhang, Z Yang, H Liu, T Zhang, T Başar IEEE Transactions on Automatic Control, 2018	106*	2018
Towards a theoretical foundation of policy optimization for learning control policies B Hu, K Zhang, N Li, M Mesbahi, M Fazel, T Başar Annual Review of Control, Robotics, and Autonomous Systems, 123-158, 2023	96	2023
Independent policy gradient for large-scale Markov potential games: Sharper rates, function approximation, and game-agnostic convergence D Ding, CY Wei, K Zhang, MR Jovanović International Conference on Machine Learning 162, 5166-5220, 2022	89	2022
The complexity of Markov equilibrium in stochastic games C Daskalakis, N Golowich, K Zhang The Thirty Sixth Annual Conference on Learning Theory, 4180-4234, 2023	84	2023

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