Black Box Optimization, Machine Learning, and No-Free Lunch Theorems / Panos M. Pardalos, Varvara Rasskazova, Michael N. Vrahatis editors

• Pubblicazione: Cham, : Springer, 2021
• Descrizione fisica: x, 388 p. : ill. ; 24 cm
• Soggetto topico: 68-XX - Computer science [MSC 2020]; 68T05 - Learning and adaptive systems in artificial intelligence [MSC 2020]; 00B15 - Collections of articles of miscellaneous specific interest [MSC 2020]; 90-XX - Operations research, mathematical programming [MSC 2020]; 90C59 - Approximation methods and heuristics in mathematical programming [MSC 2020]
• Soggetto non controllato: Black box optimization; Data driven computation; Data sciences problems; Deep Learning; Fuzzy Optimization; Machine learning; No-free lunch theorems; Non-free theorems in machine learning; Non-free theorems in optimization; Stochastic Optimization; Tuning algorithms
• Persona (resp. second.): Pardalos, Panos M.; Rasskazova, Varvara; Vrahatis, Michael N.
• Titolo autorizzato: Black box optimization, machine learning, and no-free lunch theorems
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: VAN0274601
• Lo trovi qui: Univ. Vanvitelli
• Localizzazioni e accesso elettronico: https://doi.org/10.1007/978-3-030-66515-9
• Serie: Springer optimization and its applications Berlin [etc.] . -Springer , 2006- ; 170