25 citations · 25 across the 1 of their papers we have counts for
7 papers
A Practical Guide of Off-Policy Evaluation for Bandit Problems
Masahiro Kato, Kenshi Abe, Kaito Ariu +1
Off-policy evaluation (OPE) is the problem of estimating the value of a target policy from samples obtained via different policies. Recently, applying OPE methods for bandit proble…
A Feedback Shift Correction in Predicting Conversion Rates under Delayed Feedback
Shota Yasui, Gota Morishita, Komei Fujita +1
In display advertising, predicting the conversion rate, that is, the probability that a user takes a predefined action on an advertiser's website, such as purchasing goods is funda…
Off-Policy Evaluation and Learning for External Validity under a Covariate Shift
Masahiro Kato, Masatoshi Uehara, Shota Yasui
We consider evaluating and training a new policy for the evaluation data by using the historical data obtained from a different policy. The goal of off-policy evaluation (OPE) is t…
Dual Learning Algorithm for Delayed Conversions
Yuta Saito, Gota Morishita, Shota Yasui
In display advertising, predicting the conversion rate (CVR), meaning the probability that a user takes a predefined action on an advertiser's website, is a fundamental task for es…
Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference Models
Yuta Saito, Shota Yasui
We study the model selection problem in conditional average treatment effect (CATE) prediction. Unlike previous works on this topic, we focus on preserving the rank order of the pe…
Fatigue-Aware Ad Creative Selection
Daisuke Moriwaki, Komei Fujita, Shota Yasui +1
In online display advertising, selecting the most effective ad creative (ad image) for each impression is a crucial task for DSPs (Demand-Side Platforms) to fulfill their goals (cl…