650 citations · 1.3k across the 33 of their papers we have counts for
5 papers · 2 filters
Global Convergence of Direct Policy Search for State-Feedback Robust Control: A Revisit of Nonsmooth Synthesis with Goldstein Subdifferential
Xingang Guo, Bin Hu
Direct policy search has been widely applied in modern reinforcement learning and continuous control. However, the theoretical properties of direct policy search on nonsmooth robus…
Towards a Theoretical Foundation of Policy Optimization for Learning Control Policies
Bin Hu, Kaiqing Zhang, Na Li +3
Gradient-based methods have been widely used for system design and optimization in diverse application domains. Recently, there has been a renewed interest in studying theoretical…
Provable Acceleration of Heavy Ball beyond Quadratics for a Class of Polyak-Łojasiewicz Functions when the Non-Convexity is Averaged-Out
Jun-Kun Wang, Chi-Heng Lin, Andre Wibisono +1
Heavy Ball (HB) nowadays is one of the most popular momentum methods in non-convex optimization. It has been widely observed that incorporating the Heavy Ball dynamic in gradient-b…
Connectivity of the Feasible and Sublevel Sets of Dynamic Output Feedback Control with Robustness Constraints
Bin Hu, Yang Zheng
This paper considers the optimization landscape of linear dynamic output feedback control with robustness constraints. We consider the feasible set of all the…
Convex Programs and Lyapunov Functions for Reinforcement Learning: A Unified Perspective on the Analysis of Value-Based Methods
Xingang Guo, Bin Hu
Value-based methods play a fundamental role in Markov decision processes (MDPs) and reinforcement learning (RL). In this paper, we present a unified control-theoretic framework for…