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Found 7 papers, 0 papers with code
Aspect-Similarity-Aware Historical Influence Modeling for Rating Prediction
Previous laboratory studies have indicated that the ratings recorded by these systems differ from the actual evaluations of the users, owing to the influence of historical ratings in the system.
Online Evaluation Methods for the Causal Effect of Recommendations
In contrast to conventional interleaving methods, we measure the outcomes of both items on an interleaved list and items not on the interleaved list, since the causal effect is the difference between outcomes with and without recommendations.
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.
Approximation Theory Based Methods for RKHS Bandits
The RKHS bandit problem (also called kernelized multi-armed bandit problem) is an online optimization problem of non-linear functions with noisy feedback.
An Intuitionistic Set-theoretical Model of Fully Dependent CCω
Werner's set-theoretical model is one of the simplest models of CIC.
Logic in Computer Science Logic
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.
