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A multiple-play bandit algorithm applied to recommender systems

Louëdec, Jonathan and Chevalier, Max and Mothe, Josiane and Garivier, Aurélien and Gerchinovitz, Sébastien A multiple-play bandit algorithm applied to recommender systems. (2015) In: 28th International Florida Artificial Intelligence Research Society (FLAIRS 2015), 18 May 2015 - 20 May 2015 (Hollywood, United States).

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Abstract

For several web tasks such as ad placement or e-commerce, recommender systems must recommend multiple items to their users-such problems can be modeled as bandits with multiple plays. State-of-the-art methods require running as many single-play bandit algorithms as there are items to recommend. On the contrary, some recent theoretical work in the machine learning literature designed new algorithms to address the multiple-play case directly. These algorithms were proved to have strong theoretical guarantees. In this paper we compare one such multiple-play algorithm with previous methods. We show on two real-world datasets that the multiple-play algorithm we use converges to equivalent values but learns about three times faster than state-of-the-art methods. We also show that carefully adapting these earlier methods can improve their performance.

Item Type:Conference or Workshop Item (Paper)
Additional Information:This papers appears in Proceedings of the 28th International Florida Artificial Intelligence Research Society Conference ISBN 978-1-57735-730-8 The original PDF is available at: https://www.aaai.org/ocs/index.php/FLAIRS/FLAIRS15/paper/view/10385
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UPS (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
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Deposited By: IRIT IRIT
Deposited On:01 Dec 2017 10:17

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