Partial Bandit and Semi-Bandit: Making the Most Out of Scarce Users' Feedback

Recent works on Multi-Armed Bandits (MAB) and Combinatorial Multi-Armed Bandits (COM-MAB) show good results on a global accuracy metric. This can be achieved, in the case of recommender systems, with personalization. However, with a combinatorial online learning approach, personalization implies a l...

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Veröffentlicht in:	arXiv.org 2020-09
Hauptverfasser:	Letard, Alexandre, Amghar, Tassadit, Camp, Olivier, Gutowski, Nicolas
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Combinatorial analysis Distance learning Feedback Machine learning Recommender systems User feedback
Online-Zugang:	Volltext
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