Warm Starting Bayesian Optimization

11 Aug 2016Matthias PoloczekJialei WangPeter I. Frazier

We develop a framework for warm-starting Bayesian optimization, that reduces the solution time required to solve an optimization problem that is one in a sequence of related problems. This is useful when optimizing the output of a stochastic simulator that fails to provide derivative information, for which Bayesian optimization methods are well-suited... (read more)

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