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cs.LG2026
Bellman Residual Minimization for Control: Geometry, Stationarity, and Convergence
Donghwan Lee, Hyukjun Yang
Markov decision problems are most commonly solved via dynamic programming. Another approach is Bellman residual minimization, which directly minimizes the squared Bellman residual…
cs.LG2026
Contraction-Aligned Analysis of Soft Bellman Residual Minimization with Weighted Lp-Norm for Markov Decision Problem
Hyukjun Yang, Han-Dong Lim, Donghwan Lee
The problem of solving Markov decision processes under function approximation remains a fundamental challenge, even under linear function approximation settings. A key difficulty a…
cs.LG2026
Periodic Regularized Q-Learning
Hyukjun Yang, Han-Dong Lim, Donghwan Lee
In reinforcement learning (RL), Q-learning is a fundamental algorithm whose convergence is guaranteed in the tabular setting. However, this convergence guarantee does not hold unde…