48 citations · 48 across the 1 of their papers we have counts for
2 papers
cs.LG2020★ 48 cited
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…
cs.LG2020
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…