Versions of Gradient Temporal Difference Learning. - Donghwan Lee 002; Han-Dong Lim; Jihoon Park; Okyong Choi (CoRR, 2021)

Regularized Q-learning. - Han-Dong Lim; Do Wan Kim; Donghwan Lee 002 (CoRR, 2022)

Backstepping Temporal Difference Learning. - Han-Dong Lim; Donghwan Lee 002 (ICLR, 2023)

Temporal Difference Learning with Experience Replay. - Han-Dong Lim; Donghwan Lee 002 (CoRR, 2023)

A primal-dual perspective for distributed TD-learning. - Han-Dong Lim; Donghwan Lee 002 (CoRR, 2023)

New Versions of Gradient Temporal-Difference Learning. - Donghwan Lee 002; Han-Dong Lim; Jihoon Park; Okyong Choi (IEEE Trans. Autom. Control., 2023)

Continuous-Time Distributed Dynamic Programming for Networked Multi-Agent Markov Decision Processes. - Donghwan Lee 002; Han-Dong Lim; Do Wan Kim (ICCA, 2024)

Regularized Q-Learning. - Han-Dong Lim; Donghwan Lee 002 (NeurIPS, 2024)

Finite-Time Analysis of Asynchronous Q-Learning Under Diminishing Step-Size From Control-Theoretic View. - Han-Dong Lim; Donghwan Lee 002 (IEEE Access, 2024)

Finite-Time Error Analysis of Online Model-Based Q-Learning with a Relaxed Sampling Model. - Han-Dong Lim; HyeAnn Lee; Donghwan Lee 002 (CoRR, 2024)

A finite time analysis of distributed Q-learning. - Han-Dong Lim; Donghwan Lee 002 (CoRR, 2024)

Finite-Time Analysis of Temporal Difference Learning with Experience Replay. - Han-Dong Lim; Donghwan Lee 002 (Trans. Mach. Learn. Res., 2024)

Analysis of Off-Policy n-Step TD-Learning with Linear Function Approximation. - Han-Dong Lim; Donghwan Lee 002 (CoRR, 2025)

Understanding the theoretical properties of projected Bellman equation, linear Q-learning, and approximate value iteration. - Han-Dong Lim; Donghwan Lee 002 (CoRR, 2025)