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1 Ergebnisse
1
Impatient Bandits: Optimizing Recommendations for the Long-..:
, In:
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
,
McDonald, Thomas M.
;
Maystre, Lucas
;
Lalmas, Mounia
.. - p. 1687-1697 , 2023
Link:
https://dl.acm.org/doi/10.1145/3580305.3599386
RT T1 <cTitle>Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining</cTitle>: T1 <Title>Impatient Bandits: Optimizing Recommendations for the Long-Term Without Delay</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3599386&Exemplar=1&LAN=DE A1 McDonald, Thomas M. A1 Maystre, Lucas A1 Lalmas, Mounia A1 Russo, Daniel A1 Ciosek, Kamil PB ACM YR 2023 K1 bayesian modeling K1 multi-armed bandits K1 recommender systems K1 Information systems K1 Information retrieval K1 Retrieval tasks and goals K1 Recommender systems K1 Mathematics of computing K1 Probability and statistics K1 Probabilistic inference problems K1 Computing methodologies K1 Machine learning K1 Learning paradigms K1 Reinforcement learning K1 Sequential decision making SP 1687 OP 1697 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3580305.3599386 DO https://dl.acm.org/doi/10.1145/3580305.3599386 SF ELIB - SuUB Bremen
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