output
20172020
most citedUnbiased Learning for the Causal Effect of Recommendation

48 citations

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Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

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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★ 1 cited

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…