Temporal Difference Learning as Gradient Splitting

27 October 2020

Papers citing "Temporal Difference Learning as Gradient Splitting"

14 / 14 papers shown

Title
Multi-agent Markov Entanglement Shuze Chen Tianyi Peng 47 0 0 03 Jun 2025
A Finite-Time Analysis of TD Learning with Linear Function Approximation without Projections nor Strong Convexity Wei-Cheng Lee Francesco Orabona 23 0 0 01 Jun 2025
On The Global Convergence Of Online RLHF With Neural Parametrization Mudit Gaur Amrit Singh Bedi Raghu Pasupathy Vaneet Aggarwal 77 1 0 21 Oct 2024
One-Shot Averaging for Distributed TD( $λ$ ) Under Markov Sampling Haoxing Tian I. Paschalidis Alexander Olshevsky OffRL 86 4 0 13 Mar 2024
A Simple Finite-Time Analysis of TD Learning with Linear Function Approximation Aritra Mitra 81 5 0 04 Mar 2024
On the Performance of Temporal Difference Learning With Neural Networks Haoxing Tian I. Paschalidis Alexander Olshevsky 69 5 0 08 Dec 2023
On the Second-Order Convergence of Biased Policy Gradient Algorithms Siqiao Mu Diego Klabjan 76 2 0 05 Nov 2023
On First-Order Meta-Reinforcement Learning with Moreau Envelopes Taha Toghani Sebastian Perez-Salazar César A. Uribe 100 2 0 20 May 2023
Federated Temporal Difference Learning with Linear Function Approximation under Environmental Heterogeneity Han Wang A. Mitra Hamed Hassani George J. Pappas James Anderson FedML 87 23 0 04 Feb 2023
Temporal Difference Learning with Compressed Updates: Error-Feedback meets Reinforcement Learning A. Mitra George J. Pappas Hamed Hassani 64 12 0 03 Jan 2023
Closing the gap between SVRG and TD-SVRG with Gradient Splitting Arsenii Mustafin Alexander Olshevsky I. Paschalidis 31 1 0 29 Nov 2022
Approximate discounting-free policy evaluation from transient and recurrent states Vektor Dewanto M. Gallagher OffRL 18 0 0 08 Apr 2022
A Small Gain Analysis of Single Timescale Actor Critic Alexander Olshevsky Bahman Gharesifard 104 20 0 04 Mar 2022
Distributed TD(0) with Almost No Communication R. Liu Alexander Olshevsky FedML 75 16 0 16 Apr 2021