8 citations · 9 across the 3 of their papers we have counts for
6 papers
Finite-Time Analysis for Double Q-learning
Huaqing Xiong, Lin Zhao, Yingbin Liang +1
Although Q-learning is one of the most successful algorithms for finding the best action-value function (and thus the optimal policy) in reinforcement learning, its implementation…
Momentum Q-learning with Finite-Sample Convergence Guarantee
Bowen Weng, Huaqing Xiong, Lin Zhao +2
Existing studies indicate that momentum ideas in conventional optimization can be used to improve the performance of Q-learning algorithms. However, the finite-sample analysis for…
Non-asymptotic Convergence of Adam-type Reinforcement Learning Algorithms under Markovian Sampling
Huaqing Xiong, Tengyu Xu, Yingbin Liang +1
Despite the wide applications of Adam in reinforcement learning (RL), the theoretical convergence of Adam-type RL algorithms has not been established. This paper provides the first…
Momentum-based Accelerated Q-learning
Bowen Weng, Lin Zhao, Huaqing Xiong +1
This paper studies accelerated algorithms for Q-learning. We propose an acceleration scheme by incorporating the historical iterates of the Q-function. The idea is conceptually ins…
Accelerated Target Updates for Q-learning
Bowen Weng, Huaqing Xiong, Wei Zhang
This paper studies accelerations in Q-learning algorithms. We propose an accelerated target update scheme by incorporating the historical iterates of Q functions. The idea is conce…
Analytical Convergence Regions of Accelerated Gradient Descent in Nonconvex Optimization under Regularity Condition
Huaqing Xiong, Yuejie Chi, Bin Hu +1
There is a growing interest in using robust control theory to analyze and design optimization and machine learning algorithms. This paper studies a class of nonconvex optimization…