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Theses

Bandit algorithms for recommender system optimization

Abstract : In this PhD thesis, we study the optimization of recommender systems with the objective of providing more refined suggestions of items for a user to benefit.The task is modeled using the multi-armed bandit framework.In a first part, we look upon two problems that commonly occured in recommendation systems: the large number of items to handle and the management of sponsored contents.In a second part, we investigate the empirical performance of bandit algorithms and especially how to tune conventional algorithm to improve results in stationary and non-stationary environments that arise in practice.This leads us to analyze both theoretically and empirically the greedy algorithm that, in some cases, outperforms the state-of-the-art.
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https://tel.archives-ouvertes.fr/tel-03148304
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Submitted on : Monday, February 22, 2021 - 10:25:14 AM
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  • HAL Id : tel-03148304, version 1

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Matthieu Jedor. Bandit algorithms for recommender system optimization. General Mathematics [math.GM]. Université Paris-Saclay, 2020. English. ⟨NNT : 2020UPASM027⟩. ⟨tel-03148304⟩

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