48 citations · 48 across the 4 of their papers we have counts for
6 papers
Online Evaluation Methods for the Causal Effect of Recommendations
Masahiro Sato
Evaluating the causal effect of recommendations is an important objective because the causal effect on user interactions can directly leads to an increase in sales and user engagem…
Causality-Aware Neighborhood Methods for Recommender Systems
Masahiro Sato, Sho Takemori, Janmajay Singh +1
The business objectives of recommenders, such as increasing sales, are aligned with the causal effect of recommendations. Previous recommenders targeting for the causal effect empl…
Approximation Theory Based Methods for RKHS Bandits
Sho Takemori, Masahiro Sato
The RKHS bandit problem (also called kernelized multi-armed bandit problem) is an online optimization problem of non-linear functions with noisy feedback. Although the problem has…
Unbiased Learning for the Causal Effect of Recommendation
Masahiro Sato, Sho Takemori, Janmajay Singh +1
Increasing users' positive interactions, such as purchases or clicks, is an important objective of recommender systems. Recommenders typically aim to select items that users will i…
Submodular Bandit Problem Under Multiple Constraints
Sho Takemori, Masahiro Sato, Takashi Sonoda +2
The linear submodular bandit problem was proposed to simultaneously address diversified retrieval and online learning in a recommender system. If there is no uncertainty, this prob…
Predicting Triple Scoring with Crowdsourcing-specific Features - The fiddlehead Triple Scorer at WSDM Cup 2017
Masahiro Sato
The Triple Scoring Task at the WSDM Cup 2017 involves the prediction of the relevance scores between persons and professions/nationalities. The ground truth of the relevance scores…