Decision-making in the face of uncertainty is a challenge in machine learning, and the multi-armed bandit model is a common framework to address it. This comprehensive introduction is an excellent reference for established researchers and a resource for g
LATTIMORE, TOR (UNIVERSITY OF ALBERTA),SZEPESVARI, CSABA (UNIVERSITY OF ALBERTA)
Bandit Algorithms
Decision-making in the face of uncertainty is a challenge in machine learning, and the multi-armed bandit model is a common framework to address it. This comprehensive introduction is an excellent reference for established researchers and a resource for g
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9781108486828Mladinska knjiga ID
9781108486828Leto izida
2020Datum izida
16.07.2020Število strani
536Status dobavljivosti
7-10 delovnih dniZaložnik
Cambridge University PressAvtor
Lattimore, Tor (University of Alberta),Szepesvari, Csaba (University of Alberta)Dimenzije
181 x 253 x 35BIC
KCC,PBU,UMB,UYA,UYQMOpis
Decision-making in the face of uncertainty is a challenge in machine learning, and the multi-armed bandit model is a common framework to address it. This comprehensive introduction is an excellent reference for established researchers and a resource for graduate students interested in exploring stochastic, adversarial and Bayesian frameworks. 536 pages, Worked examples or Exercises
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