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cs.LG2026
Limiting-Kernel Q(): Bridging Short and Long Horizons
Tolga Ok, Arman Sharifi Kolarijani, Peyman Mohajerin Esfahani +1
In reinforcement learning, more accurate policy evaluation has been frequently shown to improve downstream policy optimization performance. For tractability, most value estimators…
cs.LG2025
Offline Reinforcement Learning via Inverse Optimization
Ioannis Dimanidis, Tolga Ok, Peyman Mohajerin Esfahani
Inspired by the recent successes of Inverse Optimization (IO) across various application domains, we propose a novel offline Reinforcement Learning (ORL) algorithm for continuous s…
cs.LG2024
Scalable Kernel Inverse Optimization
Youyuan Long, Tolga Ok, Pedro Zattoni Scroccaro +1
Inverse Optimization (IO) is a framework for learning the unknown objective function of an expert decision-maker from a past dataset. In this paper, we extend the hypothesis class…