engMartinez-Cantin, R.BayesOpt: A Bayesian optimization library for nonlinear optimization, experimental design and banditsART-2014-89009BayesOpt 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.2014http://zaguan.unizar.es/record/131432http://zaguan.unizar.es/record/131432oai:zaguan.unizar.es:131432JOURNAL OF MACHINE LEARNING RESEARCH 15 (2014), 3735-3739byhttp://creativecommons.org/licenses/by/3.0/es/info:eu-repo/semantics/openAccess