3 papers
stat.ML2025
Off-policy Evaluation with Deeply-abstracted States
Meiling Hao, Pingfan Su, Liyuan Hu +3
Off-policy evaluation (OPE) is crucial for assessing a target policy's impact offline before its deployment. However, achieving accurate OPE in large state spaces remains challengi…
stat.ML2025
To Switch or Not to Switch? Balanced Policy Switching in Offline Reinforcement Learning
Tao Ma, Xuzhi Yang, Zoltan Szabo
Reinforcement learning (RL) -- finding the optimal behaviour (also referred to as policy) maximizing the collected long-term cumulative reward -- is among the most influential appr…
stat.ML2024
Random Fourier Signature Features
Csaba Toth, Harald Oberhauser, Zoltan Szabo
Tensor algebras give rise to one of the most powerful measures of similarity for sequences of arbitrary length called the signature kernel accompanied with attractive theoretical g…