Bayesian and High-Dimensional Global Optimization / Anatoly Zhigljavsky, Antanas Žilinskas

• Autore: Zhigljavsky, Anatoly
• Pubblicazione: Cham, : Springer, 2021
• Descrizione fisica: viii, 118 p. : ill. ; 24 cm
• Soggetto topico: 62F15 - Bayesian inference [MSC 2020]; 65K05 - Numerical mathematical programming methods [MSC 2020]; 90-XX - Operations research, mathematical programming [MSC 2020]; 90C15 - Stochastic programming [MSC 2020]; 90C26 - Nonconvex programming, global optimization [MSC 2020]; 90C59 - Approximation methods and heuristics in mathematical programming [MSC 2020]
• Soggetto non controllato: Bayesian global optimization; Expensive black-box functions; Global optimization; Global random search; High-dimensional optimization; Matrix theory; Multidimensional spaces and sets; P-algorithm
• Altri autori: Žilinskas, Antanas
• Titolo autorizzato: Bayesian and High-Dimensional Global Optimization
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: VAN00274585
• Lo trovi qui: Univ. Vanvitelli
• Localizzazioni e accesso elettronico: https://doi.org/10.1007/978-3-030-64712-4
• Serie: SpringerBriefs in optimization Berlin [etc.] . -Springer , 2012-