57 citations · 106 across the 10 of their papers we have counts for
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cs.AI2025
Safely Exploring Novel Actions in Recommender Systems via Deployment-Efficient Policy Learning
Haruka Kiyohara, Yusuke Narita, Yuta Saito +2
In many real recommender systems, novel items are added frequently over time. The importance of sufficiently presenting novel actions has widely been acknowledged for improving lon…
cs.AI2021★ 1 cited
Data-Driven Off-Policy Estimator Selection: An Application in User Marketing on An Online Content Delivery Service
Yuta Saito, Takuma Udagawa, Kei Tateno
Off-policy evaluation (OPE) is the method that attempts to estimate the performance of decision making policies using historical data generated by different policies without conduc…