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2020 – today
- 2024
[j7]Zaiwei Chen
, Siva Theja Maguluri, Sanjay Shakkottai, Karthikeyan Shanmugam:
A Lyapunov Theory for Finite-Sample Guarantees of Markovian Stochastic Approximation. Oper. Res. 72(4): 1352-1367 (2024)- [i17]Ruiyang Jin, Zaiwei Chen, Yiheng Lin, Jie Song, Adam Wierman:
Approximate Global Convergence of Independent Learning in Multi-Agent Systems. CoRR abs/2405.19811 (2024) - [i16]Zaiwei Chen, Kaiqing Zhang, Eric Mazumdar, Asuman E. Ozdaglar, Adam Wierman:
Last-Iterate Convergence of Payoff-Based Independent Learning in Zero-Sum Stochastic Games. CoRR abs/2409.01447 (2024) - 2023
- [j6]Yizhou Zhang, Guannan Qu, Pan Xu, Yiheng Lin, Zaiwei Chen, Adam Wierman:
Global Convergence of Localized Policy Iteration in Networked Multi-Agent Reinforcement Learning. Proc. ACM Meas. Anal. Comput. Syst. 7(1): 13:1-13:51 (2023) - [j5]Zaiwei Chen, John-Paul Clarke, Siva Theja Maguluri:
Target Network and Truncation Overcome the Deadly Triad in \(\boldsymbol{Q}\)-Learning. SIAM J. Math. Data Sci. 5(4): 1078-1101 (2023) - [c8]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 - [c7]Yizhou Zhang, Guannan Qu, Pan Xu, Yiheng Lin, Zaiwei Chen, Adam Wierman:
Global Convergence of Localized Policy Iteration in Networked Multi-Agent Reinforcement Learning. SIGMETRICS (Abstracts) 2023: 83-84 - [c6]Zhaoyi Zhou, Zaiwei Chen, Yiheng Lin, Adam Wierman:
Convergence rates for localized actor-critic in networked Markov potential games. UAI 2023: 2563-2573 - [i15]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 abs/2303.03100 (2023) - [i14]Zhaoyi Zhou, Zaiwei Chen, Yiheng Lin, Adam Wierman:
Convergence Rates for Localized Actor-Critic in Networked Markov Potential Games. CoRR abs/2303.04865 (2023) - [i13]Zaiwei Chen, Siva Theja Maguluri, Martin Zubeldia:
Concentration of Contractive Stochastic Approximation: Additive and Multiplicative Noise. CoRR abs/2303.15740 (2023) - [i12]Zaiwei Chen, Kaiqing Zhang, Eric Mazumdar, Asuman E. Ozdaglar, Adam Wierman:
Two-Timescale Q-Learning with Function Approximation in Zero-Sum Stochastic Games. CoRR abs/2312.04905 (2023) - 2022
- [j4]Zaiwei Chen, Sheng Zhang, Thinh T. Doan, John-Paul Clarke, Siva Theja Maguluri:
Finite-sample analysis of nonlinear stochastic approximation with applications in reinforcement learning. Autom. 146: 110623 (2022) - [j3]Zaiwei Chen, Sajad Khodadadian, Siva Theja Maguluri:
Finite-Sample Analysis of Off-Policy Natural Actor-Critic With Linear Function Approximation. IEEE Control. Syst. Lett. 6: 2611-2616 (2022) - [j2]Zaiwei Chen, Shancong Mou, Siva Theja Maguluri:
Stationary Behavior of Constant Stepsize SGD Type Algorithms: An Asymptotic Characterization. Proc. ACM Meas. Anal. Comput. Syst. 6(1): 19:1-19:24 (2022) - [j1]Zaiwei Chen:
A Unified Lyapunov Framework for Finite-Sample Analysis of Reinforcement Learning Algorithms. SIGMETRICS Perform. Evaluation Rev. 50(3): 12-15 (2022) - [c5]Zaiwei Chen, Siva Theja Maguluri:
Sample Complexity of Policy-Based Methods under Off-Policy Sampling and Linear Function Approximation. AISTATS 2022: 11195-11214 - [c4]Zaiwei Chen, Shancong Mou, Siva Theja Maguluri:
Stationary Behavior of Constant Stepsize SGD Type Algorithms: An Asymptotic Characterization. SIGMETRICS (Abstracts) 2022: 109-110 - [i11]Zaiwei Chen, John-Paul Clarke, Siva Theja Maguluri:
Target Network and Truncation Overcome The Deadly triad in Q-Learning. CoRR abs/2203.02628 (2022) - [i10]Zaiwei Chen, Siva Theja Maguluri:
Sample Complexity of Policy-Based Methods under Off-Policy Sampling and Linear Function Approximation. CoRR abs/2208.03247 (2022) - [i9]Yizhou Zhang, Guannan Qu, Pan Xu, Yiheng Lin, Zaiwei Chen, Adam Wierman:
Global Convergence of Localized Policy Iteration in Networked Multi-Agent Reinforcement Learning. CoRR abs/2211.17116 (2022) - 2021
- [c3]Sajad Khodadadian, Zaiwei Chen, Siva Theja Maguluri:
Finite-Sample Analysis of Off-Policy Natural Actor-Critic Algorithm. ICML 2021: 5420-5431 - [c2]Zaiwei Chen, Siva Theja Maguluri, Sanjay Shakkottai, Karthikeyan Shanmugam:
Finite-Sample Analysis of Off-Policy TD-Learning via Generalized Bellman Operators. NeurIPS 2021: 21440-21452 - [i8]Zaiwei Chen, Siva Theja Maguluri, Sanjay Shakkottai, Karthikeyan Shanmugam:
A Lyapunov Theory for Finite-Sample Guarantees of Asynchronous Q-Learning and TD-Learning Variants. CoRR abs/2102.01567 (2021) - [i7]Sajad Khodadadian, Zaiwei Chen, Siva Theja Maguluri:
Finite-Sample Analysis of Off-Policy Natural Actor-Critic Algorithm. CoRR abs/2102.09318 (2021) - [i6]Fanruiqi Zeng, Zaiwei Chen, John-Paul Clarke, David Goldsman:
Nested Vehicle Routing Problem: Optimizing Drone-Truck Surveillance Operations. CoRR abs/2103.01528 (2021) - [i5]Zaiwei Chen, Sajad Khodadadian, Siva Theja Maguluri:
Finite-Sample Analysis of Off-Policy Natural Actor-Critic with Linear Function Approximation. CoRR abs/2105.12540 (2021) - [i4]Zaiwei Chen, Siva Theja Maguluri, Sanjay Shakkottai, Karthikeyan Shanmugam:
Finite-Sample Analysis of Off-Policy TD-Learning via Generalized Bellman Operators. CoRR abs/2106.12729 (2021) - [i3]Zaiwei Chen, Shancong Mou, Siva Theja Maguluri:
Stationary Behavior of Constant Stepsize SGD Type Algorithms: An Asymptotic Characterization. CoRR abs/2111.06328 (2021) - 2020
- [c1]Zaiwei Chen, Siva Theja Maguluri, Sanjay Shakkottai, Karthikeyan Shanmugam:
Finite-Sample Analysis of Contractive Stochastic Approximation Using Smooth Convex Envelopes. NeurIPS 2020 - [i2]Zaiwei Chen, Siva Theja Maguluri, Sanjay Shakkottai, Karthikeyan Shanmugam:
Finite-Sample Analysis of Stochastic Approximation Using Smooth Convex Envelopes. CoRR abs/2002.00874 (2020)
2010 – 2019
- 2019
- [i1]Zaiwei Chen, Sheng Zhang, Thinh T. Doan, Siva Theja Maguluri, John-Paul Clarke:
Finite-Time Analysis of Q-Learning with Linear Function Approximation. CoRR abs/1905.11425 (2019)
Coauthor Index
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