Non-asymptotic Convergence of Adam-type Reinforcement Learning
Algorithms under Markovian Sampling

Non-asymptotic Convergence of Adam-type Reinforcement Learning Algorithms under Markovian Sampling

15 February 2020

Wei Zhang

Papers citing "Non-asymptotic Convergence of Adam-type Reinforcement Learning Algorithms under Markovian Sampling"

8 / 8 papers shown

Title
Fast Two-Time-Scale Stochastic Gradient Method with Applications in Reinforcement Learning Sihan Zeng Thinh T. Doan 56 5 0 15 May 2024
On the Stochastic (Variance-Reduced) Proximal Gradient Method for Regularized Expected Reward Optimization Ling Liang Haizhao Yang 14 1 0 23 Jan 2024
Markov Chain Score Ascent: A Unifying Framework of Variational Inference with Markovian Gradients Kyurae Kim Jisu Oh Jacob R. Gardner Adji Bousso Dieng Hongseok Kim BDL 37 8 0 13 Jun 2022
Recent Advances in Reinforcement Learning in Finance B. Hambly Renyuan Xu Huining Yang OffRL 29 168 0 08 Dec 2021
Doubly Robust Off-Policy Actor-Critic: Convergence and Optimality Tengyu Xu Zhuoran Yang Zhaoran Wang Yingbin Liang OffRL 47 24 0 23 Feb 2021
CRPO: A New Approach for Safe Reinforcement Learning with Convergence Guarantee Tengyu Xu Yingbin Liang Guanghui Lan 52 122 0 11 Nov 2020
Sample Efficient Reinforcement Learning with REINFORCE Junzi Zhang Jongho Kim Brendan O'Donoghue Stephen P. Boyd 42 101 0 22 Oct 2020
Non-asymptotic Convergence Analysis of Two Time-scale (Natural) Actor-Critic Algorithms Tengyu Xu Zhe Wang Yingbin Liang 26 57 0 07 May 2020