BayesOpt: A Bayesian optimization library for nonlinear optimization, experimental design and bandits
Martinez-Cantin, R.
Resumen: BayesOpt is a library with state-of-the-art Bayesian optimization methods to solve nonlinear optimization, stochastic bandits or sequential experimental design problems. Bayesian optimization characterized for being sample ecient as it builds a posterior distribution to capture the evidence and prior knowledge of the target function. Built in standard C++, the library is extremely ecient while being portable and
exible. It includes a common interface for C, C++, Python, Matlab and Octave.
Idioma: Inglés
Año: 2014
Publicado en: JOURNAL OF MACHINE LEARNING RESEARCH 15 (2014), 3735-3739
ISSN: 1532-4435
Factor impacto JCR: 2.473 (2014)
Categ. JCR: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE rank: 22 / 123 = 0.179 (2014) - Q1 - T1
Categ. JCR: AUTOMATION & CONTROL SYSTEMS rank: 10 / 58 = 0.172 (2014) - Q1 - T1
Tipo y forma: Article (Published version)
You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
Exportado de SIDERAL (2024-02-09-14:28:02)
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exible. It includes a common interface for C, C++, Python, Matlab and Octave.
Idioma: Inglés
Año: 2014
Publicado en: JOURNAL OF MACHINE LEARNING RESEARCH 15 (2014), 3735-3739
ISSN: 1532-4435
Factor impacto JCR: 2.473 (2014)
Categ. JCR: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE rank: 22 / 123 = 0.179 (2014) - Q1 - T1
Categ. JCR: AUTOMATION & CONTROL SYSTEMS rank: 10 / 58 = 0.172 (2014) - Q1 - T1
Tipo y forma: Article (Published version)
You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. Exportado de SIDERAL (2024-02-09-14:28:02)
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Record created 2024-02-09, last modified 2024-02-09