Discretization-free Knowledge Gradient Methods for Bayesian Optimization

20 Jul 2017 Jian Wu Peter I. Frazier

This paper studies Bayesian ranking and selection (R&S) problems with correlated prior beliefs and continuous domains, i.e. Bayesian optimization (BO). Knowledge gradient methods [Frazier et al., 2008, 2009] have been widely studied for discrete R&S problems, which sample the one-step Bayes-optimal point... (read more)

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