Zaiwei Chen - RankMe

45 papers A* 7A 3Journal 32Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Achieving ϵ CoRR Zijun Chen, Zaiwei Chen, Nian Si, Shengbo Wang
2026	J	`jnl`	Natural Hypergradient Descent: Algorithm Design, Convergence Analysis, and Parallel Implementation. CoRR Deyi Kong, Zaiwei Chen, Shuzhong Zhang, Shancong Mou
2025	J	`jnl`	A Minimal-Assumption Analysis of Q-Learning with Time-Varying Policies. CoRR Phalguni Nanda, Zaiwei Chen
2025	J	`jnl`	A Non-Asymptotic Theory of Seminorm Lyapunov Stability: From Deterministic to Stochastic Iterative Algorithms. CoRR Zaiwei Chen, Sheng Zhang, Zhe Zhang, Shaan Ul Haque, Siva Theja Maguluri
2025	J	`jnl`	An approximate policy iteration viewpoint of actor-critic algorithms. Autom. Zaiwei Chen, Siva Theja Maguluri
2025	A	`conf`	Approximate Global Convergence of Independent Learning in Multi-Agent Systems. AISTATS Ruiyang Jin, Zaiwei Chen, Yiheng Lin, Jie Song, Adam Wierman
2025	J	`jnl`	Non-Asymptotic Guarantees for Average-Reward Q-Learning with Adaptive Stepsizes. CoRR Zaiwei Chen
2025	A*	`conf`	Overcoming the Curse of Dimensionality in Reinforcement Learning Through Approximate Factorization. ICML Chenbei Lu, Laixi Shi, Zaiwei Chen, Chenye Wu, Adam Wierman
2025	J	`jnl`	Reinforcement Learning with Imperfect Transition Predictions: A Bellman-Jensen Approach. CoRR Chenbei Lu, Zaiwei Chen, Tongxin Li, Chenye Wu, Adam Wierman
2024	J	`jnl`	A Lyapunov Theory for Finite-Sample Guarantees of Markovian Stochastic Approximation. Oper. Res. Zaiwei Chen, Siva Theja Maguluri, Sanjay Shakkottai, Karthikeyan Shanmugam
2024	J	`jnl`	Approximate Global Convergence of Independent Learning in Multi-Agent Systems. CoRR Ruiyang Jin, Zaiwei Chen, Yiheng Lin, Jie Song, Adam Wierman
2024	A*	`conf`	Last-Iterate Convergence for Generalized Frank-Wolfe in Monotone Variational Inequalities. NeurIPS Zaiwei Chen, Eric Mazumdar
2024	J	`jnl`	Last-Iterate Convergence of Payoff-Based Independent Learning in Zero-Sum Stochastic Games. CoRR Zaiwei Chen, Kaiqing Zhang, Eric Mazumdar, Asuman E. Ozdaglar, Adam Wierman
2024	J	`jnl`	Overcoming the Curse of Dimensionality in Reinforcement Learning Through Approximate Factorization. CoRR Chenbei Lu, Laixi Shi, Zaiwei Chen, Chenye Wu, Adam Wierman
2024	A*	`conf`	Two-Timescale Q-Learning with Function Approximation in Zero-Sum Stochastic Games. EC Zaiwei Chen, Kaiqing Zhang, Eric Mazumdar, Asuman E. Ozdaglar, Adam Wierman
2023	A*	`conf`	A Finite-Sample Analysis of Payoff-Based Independent Learning in Zero-Sum Stochastic Games. NeurIPS Zaiwei Chen, Kaiqing Zhang, Eric Mazumdar, Asuman E. Ozdaglar, Adam Wierman
2023	J	`jnl`	A Finite-Sample Analysis of Payoff-Based Independent Learning in Zero-Sum Stochastic Games. CoRR Zaiwei Chen, Kaiqing Zhang, Eric Mazumdar, Asuman E. Ozdaglar, Adam Wierman
2023	J	`jnl`	Concentration of Contractive Stochastic Approximation: Additive and Multiplicative Noise. CoRR Zaiwei Chen, Siva Theja Maguluri, Martin Zubeldia
2023	J	`jnl`	Convergence Rates for Localized Actor-Critic in Networked Markov Potential Games. CoRR Zhaoyi Zhou, Zaiwei Chen, Yiheng Lin, Adam Wierman
2023	A	`conf`	Convergence rates for localized actor-critic in networked Markov potential games. UAI Zhaoyi Zhou, Zaiwei Chen, Yiheng Lin, Adam Wierman
2023	—	`conf`	Global Convergence of Localized Policy Iteration in Networked Multi-Agent Reinforcement Learning. SIGMETRICS (Abstracts) Yizhou Zhang, Guannan Qu, Pan Xu, Yiheng Lin, Zaiwei Chen, Adam Wierman
2023	J	`jnl`	Global Convergence of Localized Policy Iteration in Networked Multi-Agent Reinforcement Learning. Proc. ACM Meas. Anal. Comput. Syst. Yizhou Zhang, Guannan Qu, Pan Xu, Yiheng Lin, Zaiwei Chen, Adam Wierman
2023	J	`jnl`	Target Network and Truncation Overcome the Deadly Triad in \(\boldsymbol{Q}\)-Learning. SIAM J. Math. Data Sci. Zaiwei Chen, John-Paul Clarke, Siva Theja Maguluri
2023	J	`jnl`	Two-Timescale Q-Learning with Function Approximation in Zero-Sum Stochastic Games. CoRR Zaiwei Chen, Kaiqing Zhang, Eric Mazumdar, Asuman E. Ozdaglar, Adam Wierman
2022	J	`jnl`	A Unified Lyapunov Framework for Finite-Sample Analysis of Reinforcement Learning Algorithms. SIGMETRICS Perform. Evaluation Rev. Zaiwei Chen
2022	—	`—`	A Unified Lyapunov Framework for Finite-Sample Analysis of Reinforcement Learning Algorithms. Zaiwei Chen
2022	J	`jnl`	Finite-Sample Analysis of Off-Policy Natural Actor-Critic With Linear Function Approximation. IEEE Control. Syst. Lett. Zaiwei Chen, Sajad Khodadadian, Siva Theja Maguluri
2022	J	`jnl`	Finite-sample analysis of nonlinear stochastic approximation with applications in reinforcement learning. Autom. Zaiwei Chen, Sheng Zhang, Thinh T. Doan, John-Paul Clarke, Siva Theja Maguluri
2022	J	`jnl`	Global Convergence of Localized Policy Iteration in Networked Multi-Agent Reinforcement Learning. CoRR Yizhou Zhang, Guannan Qu, Pan Xu, Yiheng Lin, Zaiwei Chen, Adam Wierman
2022	A	`conf`	Sample Complexity of Policy-Based Methods under Off-Policy Sampling and Linear Function Approximation. AISTATS Zaiwei Chen, Siva Theja Maguluri
2022	J	`jnl`	Sample Complexity of Policy-Based Methods under Off-Policy Sampling and Linear Function Approximation. CoRR Zaiwei Chen, Siva Theja Maguluri
2022	—	`conf`	Stationary Behavior of Constant Stepsize SGD Type Algorithms: An Asymptotic Characterization. SIGMETRICS (Abstracts) Zaiwei Chen, Shancong Mou, Siva Theja Maguluri
2022	J	`jnl`	Stationary Behavior of Constant Stepsize SGD Type Algorithms: An Asymptotic Characterization. Proc. ACM Meas. Anal. Comput. Syst. Zaiwei Chen, Shancong Mou, Siva Theja Maguluri
2022	J	`jnl`	Target Network and Truncation Overcome The Deadly triad in Q-Learning. CoRR Zaiwei Chen, John-Paul Clarke, Siva Theja Maguluri
2021	J	`jnl`	A Lyapunov Theory for Finite-Sample Guarantees of Asynchronous Q-Learning and TD-Learning Variants. CoRR Zaiwei Chen, Siva Theja Maguluri, Sanjay Shakkottai, Karthikeyan Shanmugam
2021	A*	`conf`	Finite-Sample Analysis of Off-Policy Natural Actor-Critic Algorithm. ICML Sajad Khodadadian, Zaiwei Chen, Siva Theja Maguluri
2021	J	`jnl`	Finite-Sample Analysis of Off-Policy Natural Actor-Critic Algorithm. CoRR Sajad Khodadadian, Zaiwei Chen, Siva Theja Maguluri
2021	J	`jnl`	Finite-Sample Analysis of Off-Policy Natural Actor-Critic with Linear Function Approximation. CoRR Zaiwei Chen, Sajad Khodadadian, Siva Theja Maguluri
2021	A*	`conf`	Finite-Sample Analysis of Off-Policy TD-Learning via Generalized Bellman Operators. NeurIPS Zaiwei Chen, Siva Theja Maguluri, Sanjay Shakkottai, Karthikeyan Shanmugam
2021	J	`jnl`	Finite-Sample Analysis of Off-Policy TD-Learning via Generalized Bellman Operators. CoRR Zaiwei Chen, Siva Theja Maguluri, Sanjay Shakkottai, Karthikeyan Shanmugam
2021	J	`jnl`	Nested Vehicle Routing Problem: Optimizing Drone-Truck Surveillance Operations. CoRR Fanruiqi Zeng, Zaiwei Chen, John-Paul Clarke, David Goldsman
2021	J	`jnl`	Stationary Behavior of Constant Stepsize SGD Type Algorithms: An Asymptotic Characterization. CoRR Zaiwei Chen, Shancong Mou, Siva Theja Maguluri
2020	A*	`conf`	Finite-Sample Analysis of Contractive Stochastic Approximation Using Smooth Convex Envelopes. NeurIPS Zaiwei Chen, Siva Theja Maguluri, Sanjay Shakkottai, Karthikeyan Shanmugam
2020	J	`jnl`	Finite-Sample Analysis of Stochastic Approximation Using Smooth Convex Envelopes. CoRR Zaiwei Chen, Siva Theja Maguluri, Sanjay Shakkottai, Karthikeyan Shanmugam
2019	J	`jnl`	Finite-Time Analysis of Q-Learning with Linear Function Approximation. CoRR Zaiwei Chen, Sheng Zhang, Thinh T. Doan, Siva Theja Maguluri, John-Paul Clarke