Finite-Time Analysis of Q-Learning with Linear Function Approximation. - Zaiwei Chen; Sheng Zhang; Thinh T. Doan 001; Siva Theja Maguluri; John-Paul Clarke (CoRR, 2019)

Finite-Sample Analysis of Contractive Stochastic Approximation Using Smooth Convex Envelopes. - Zaiwei Chen; Siva Theja Maguluri; Sanjay Shakkottai; Karthikeyan Shanmugam (NeurIPS, 2020)

Finite-Sample Analysis of Stochastic Approximation Using Smooth Convex Envelopes. - Zaiwei Chen; Siva Theja Maguluri; Sanjay Shakkottai; Karthikeyan Shanmugam (CoRR, 2020)

Finite-Sample Analysis of Off-Policy Natural Actor-Critic Algorithm. - Sajad Khodadadian; Zaiwei Chen; Siva Theja Maguluri (ICML, 2021)

Finite-Sample Analysis of Off-Policy TD-Learning via Generalized Bellman Operators. - Zaiwei Chen; Siva Theja Maguluri; Sanjay Shakkottai; Karthikeyan Shanmugam (NeurIPS, 2021)

A Lyapunov Theory for Finite-Sample Guarantees of Asynchronous Q-Learning and TD-Learning Variants. - Zaiwei Chen; Siva Theja Maguluri; Sanjay Shakkottai; Karthikeyan Shanmugam (CoRR, 2021)

Nested Vehicle Routing Problem: Optimizing Drone-Truck Surveillance Operations. - Fanruiqi Zeng; Zaiwei Chen; John-Paul Clarke; David Goldsman (CoRR, 2021)

Sample Complexity of Policy-Based Methods under Off-Policy Sampling and Linear Function Approximation. - Zaiwei Chen; Siva Theja Maguluri (AISTATS, 2022)

Finite-sample analysis of nonlinear stochastic approximation with applications in reinforcement learning. - Zaiwei Chen; Sheng Zhang; Thinh T. Doan 001; John-Paul Clarke; Siva Theja Maguluri (Autom., 2022)

Target Network and Truncation Overcome The Deadly triad in Q-Learning. - Zaiwei Chen; John-Paul Clarke; Siva Theja Maguluri (CoRR, 2022)

Finite-Sample Analysis of Off-Policy Natural Actor-Critic With Linear Function Approximation. - Zaiwei Chen; Sajad Khodadadian; Siva Theja Maguluri (IEEE Control. Syst. Lett., 2022)

Stationary Behavior of Constant Stepsize SGD Type Algorithms: An Asymptotic Characterization. - Zaiwei Chen; Shancong Mou; Siva Theja Maguluri (Proc. ACM Meas. Anal. Comput. Syst., 2022)

A Unified Lyapunov Framework for Finite-Sample Analysis of Reinforcement Learning Algorithms. - Zaiwei Chen (2022)

A Unified Lyapunov Framework for Finite-Sample Analysis of Reinforcement Learning Algorithms. - Zaiwei Chen (SIGMETRICS Perform. Evaluation Rev., 2022)

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)

Convergence rates for localized actor-critic in networked Markov potential games. - Zhaoyi Zhou; Zaiwei Chen; Yiheng Lin 001; Adam Wierman (UAI, 2023)

Concentration of Contractive Stochastic Approximation: Additive and Multiplicative Noise. - Zaiwei Chen; Siva Theja Maguluri; Martin Zubeldia (CoRR, 2023)

Global Convergence of Localized Policy Iteration in Networked Multi-Agent Reinforcement Learning. - Yizhou Zhang; Guannan Qu; Pan Xu 002; Yiheng Lin 001; Zaiwei Chen; Adam Wierman (Proc. ACM Meas. Anal. Comput. Syst., 2023)

Target Network and Truncation Overcome the Deadly Triad in ( boldsymbol{Q} )-Learning. - Zaiwei Chen; John-Paul Clarke; Siva Theja Maguluri (SIAM J. Math. Data Sci., 2023)

Last-Iterate Convergence for Generalized Frank-Wolfe in Monotone Variational Inequalities. - Zaiwei Chen; Eric Mazumdar (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)

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)

Overcoming the Curse of Dimensionality in Reinforcement Learning Through Approximate Factorization. - Chenbei Lu; Laixi Shi; Zaiwei Chen; Chenye Wu; Adam Wierman (CoRR, 2024)

A Lyapunov Theory for Finite-Sample Guarantees of Markovian Stochastic Approximation. - Zaiwei Chen; Siva Theja Maguluri; Sanjay Shakkottai; Karthikeyan Shanmugam (Oper. Res., 2024)

Approximate Global Convergence of Independent Learning in Multi-Agent Systems. - Ruiyang Jin; Zaiwei Chen; Yiheng Lin 001; Jie Song 002; Adam Wierman (AISTATS, 2025)

An approximate policy iteration viewpoint of actor-critic algorithms. - Zaiwei Chen; Siva Theja Maguluri (Autom., 2025)

A Non-Asymptotic Theory of Seminorm Lyapunov Stability: From Deterministic to Stochastic Iterative Algorithms. - Zaiwei Chen; Sheng Zhang; Zhe Zhang; Shaan Ul Haque; Siva Theja Maguluri (CoRR, 2025)

Non-Asymptotic Guarantees for Average-Reward Q-Learning with Adaptive Stepsizes. - Zaiwei Chen (CoRR, 2025)