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Causality-Aware Neighborhood Methods for Recommender Systems
In this work, we unify traditional neighborhood recommendation methods with the matching estimator, and develop robust ranking methods for the causal effect of recommendations.
Unbiased Learning for the Causal Effect of Recommendation
This paper proposes an unbiased learning framework for the causal effect of recommendation.
Submodular Bandit Problem Under Multiple Constraints
Thus, motivated by diversified retrieval considering budget constraints, we introduce a submodular bandit problem under the intersection of $l$ knapsacks and a $k$-system constraint.
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