Han-Dong Lim

Orcid: 0000-0002-1515-5836

According to our database1, Han-Dong Lim authored at least 17 papers between 2021 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
A Switching System Theory of Q-Learning with Linear Function Approximation.
CoRR, May, 2026

Contraction-Aligned Analysis of Soft Bellman Residual Minimization with Weighted Lp-Norm for Markov Decision Problem.
CoRR, April, 2026

Periodic Regularized Q-Learning.
CoRR, February, 2026

2025
Understanding the theoretical properties of projected Bellman equation, linear Q-learning, and approximate value iteration.
CoRR, April, 2025

Analysis of Off-Policy <i>n</i>-Step TD-Learning with Linear Function Approximation.
CoRR, February, 2025

A Primal-dual Perspective for Distributed TD-learning.
Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025

2024
Finite-Time Analysis of Temporal Difference Learning with Experience Replay.
Trans. Mach. Learn. Res., 2024

A finite time analysis of distributed Q-learning.
CoRR, 2024

Finite-Time Error Analysis of Online Model-Based Q-Learning with a Relaxed Sampling Model.
CoRR, 2024

Finite-Time Analysis of Asynchronous Q-Learning Under Diminishing Step-Size From Control-Theoretic View.
IEEE Access, 2024

Regularized Q-Learning.
Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Continuous-Time Distributed Dynamic Programming for Networked Multi-Agent Markov Decision Processes.
Proceedings of the 18th IEEE International Conference on Control & Automation, 2024

2023
New Versions of Gradient Temporal-Difference Learning.
IEEE Trans. Autom. Control., August, 2023

Temporal Difference Learning with Experience Replay.
CoRR, 2023

Backstepping Temporal Difference Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Regularized Q-learning.
CoRR, 2022

2021
Versions of Gradient Temporal Difference Learning.
CoRR, 2021


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