37 citations · 183 across the 28 of their papers we have counts for
28 papers
On the Optimal Lower and Upper Complexity Bounds for a Class of Composite Optimization Problems
Zhenyuan Zhu, Fan Chen, Junyu Zhang +1
We study the optimal lower and upper complexity bounds for finding approximate solutions to the composite problem , where is smooth and is convex. Giv…
Offline Meta Reinforcement Learning with In-Distribution Online Adaptation
Jianhao Wang, Jin Zhang, Haozhe Jiang +3
Recent offline meta-reinforcement learning (meta-RL) methods typically utilize task-dependent behavior policies (e.g., training RL agents on each individual task) to collect a mult…
Efficient First Order Method for Saddle Point Problems with Higher Order Smoothness
Nuozhou Wang, Junyu Zhang, Shuzhong Zhang
This paper studies the complexity of finding approximate stationary points for the smooth nonconvex-strongly-concave (NC-SC) saddle point problem: . Under the s…
Gauss-Newton Temporal Difference Learning with Nonlinear Function Approximation
Zhifa Ke, Junyu Zhang, Zaiwen Wen
In this paper, a Gauss-Newton Temporal Difference (GNTD) learning method is proposed to solve the Q-learning problem with nonlinear function approximation. In each iteration, our m…
A Unified Primal-Dual Algorithm Framework for Inequality Constrained Problems
Zhenyuan Zhu, Fan Chen, Junyu Zhang +1
In this paper, we propose a unified primal-dual algorithm framework based on the augmented Lagrangian function for composite convex problems with conic inequality constraints. The…
A Near-Optimal Primal-Dual Method for Off-Policy Learning in CMDP
Fan Chen, Junyu Zhang, Zaiwen Wen
As an important framework for safe Reinforcement Learning, the Constrained Markov Decision Process (CMDP) has been extensively studied in the recent literature. However, despite th…