3 papers
cs.LG2026
Non-Convex Sparse Reinforcement Learning via Non-Monotone Inclusions
Kyohei Suzuki, Konstantinos Slavakis
This work delivers two key contributions: one to efficient feature selection in reinforcement learning (RL), the other to the theory of non-monotone inclusions. On the RL side, the…
cs.LG2026
External Division of Two Bregman Proximity Operators for Poisson Inverse Problems
Kazuki Haishima, Kyohei Suzuki, Konstantinos Slavakis
This paper presents a novel method for recovering sparse vectors from linear models corrupted by Poisson noise. The contribution is twofold. First, an operator defined via the exte…
cs.LG2025
Nonconvex Regularization for Feature Selection in Reinforcement Learning
Kyohei Suzuki, Konstantinos Slavakis
This work proposes an efficient batch algorithm for feature selection in reinforcement learning (RL) with theoretical convergence guarantees. To mitigate the estimation bias inhere…