57 citations · 106 across the 10 of their papers we have counts for
3 papers · 1 filter
Offline Contextual Bandits in the Presence of New Actions
Ren Kishimoto, Tatsuhiro Shimizu, Kazuki Kawamura +6
Automated decision-making algorithms drive applications such as recommendation systems and search engines. These algorithms often rely on off-policy contextual bandits or off-polic…
Off-Policy Evaluation for Ranking Policies under Deterministic Logging Policies
Koichi Tanaka, Kazuki Kawamura, Takanori Muroi +6
Off-Policy Evaluation (OPE) is an important practical problem in algorithmic ranking systems, where the goal is to estimate the expected performance of a new ranking policy using o…
Policy-Adaptive Estimator Selection for Off-Policy Evaluation
Takuma Udagawa, Haruka Kiyohara, Yusuke Narita +2
Off-policy evaluation (OPE) aims to accurately evaluate the performance of counterfactual policies using only offline logged data. Although many estimators have been developed, the…