2026
NONCONVEX REGULARIZATION FOR FEATURE SELECTION IN REINFORCEMENT LEARNING
ICASSP 2026poster
This work proposes an efficient batch algorithm for feature selection in reinforcement learning (RL) with theoretical convergence guarantees. To mitigate the estimation bias inherent in conventional regularization schemes, the first contribution extends policy evaluation within the classical least-s…