Yuta Saito
Yuta Saito
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Off-Policy Evaluation
Counterfactual Learning and Evaluation for Recommender Systems
Counterfactual estimators enable the use of existing log data to estimate how some new target recommendation policy would have …
Yuta Saito
,
Thorsten Joachims
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Evaluating the Robustness of Off-Policy Evaluation
Off-policy Evaluation (OPE), or offline evaluation in general, evaluates the performance of hypothetical policies leveraging only …
Yuta Saito
,
Takuma Udagawa
,
Haruka Kiyohara
,
Kazuki Mogi
,
Yusuke Narita
,
Kei Tateno
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Proceedings
arXiv
Optimal Off-Policy Evaluation from Multiple Logging Policies
We study off-policy evaluation (OPE) from multiple logging policies, each generating a dataset of fixed size, i.e., stratified …
Nathan Kallus
,
Yuta Saito
,
Masatoshi Uehara
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Proceedings
arXiv
Doubly Robust Estimator for Ranking Metrics with Post-Click Conversions
Post-click conversion, a pre-defined action on a web service after a click, is an essential form of feedback, as it directly …
Yuta Saito
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Proceedings
Data-Driven Off-Policy Estimator Selection: An Application in User Marketing on An Online Content Delivery Service
Off-policy evaluation (OPE) is the method that attempts to estimate the performance of decision making policies using historical data …
Yuta Saito
,
Takuma Udagawa
,
Kei Tateno
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arXiv
Open Bandit Pipeline
A research framework for off-policy evaluation and learning
Last updated on Feb 2, 2022
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