Yuta Saito
Yuta Saito
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2020
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
Unbiased Pairwise Learning from Biased Implicit Feedback
Implicit feedback is prevalent in real-world scenarios and is widely used in the construction of recommender systems. However, the …
Yuta Saito
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Proceedings
Unbiased lift-based bidding system
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Daisuke Moriwaki
,
Yuta Hayakawa
,
Isshu Munemasa
,
Yuta Saito
,
Akira Matsui
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arXiv
Asymmetric Tri-training for Debiasing Missing-Not-At-Random Explicit Feedback
In most real-world recommender systems, the observed rating data are subject to selection bias, and the data are thus …
Yuta Saito
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Proceedings
Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference Models
We study the model selection problem in mph{conditional average treatment effect} (CATE) prediction. Unlike previous works on this …
Yuta Saito
,
Shota Yasui
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Proceedings
Dual Learning Algorithm for Delayed Conversions
In display advertising, predicting the conversion rate (CVR), meaning the probability that a user takes a predefined action on an …
Yuta Saito
,
Gota Morishita
,
Shota Yasui
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Slides
Proceedings
Cost-Effective and Stable Policy Optimization Algorithm for Uplift Modeling with Multiple Treatments
Uplift modeling aims to optimize treatment policies and is a promising method for causal-based personalization in various domains such …
Yuta Saito
,
Hayato Sakata
,
Kazuhide Nakata
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Proceedings
Unbiased Recommender Learning from Missing-Not-At-Random Implicit Feedback
Recommender systems widely use implicit feedback such as click data because of its general availability. Although the presence of …
Yuta Saito
,
Suguru Yaginuma
,
Yuta Nishino
,
Hayato Sakata
,
Kazuhide Nakata
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