Active Bayesian Optimization: Minimizing Minimizer Entropy

Abstract

The ultimate goal of optimization is to find the minimizer of a target function. However, typical criteria for active optimization often ignore the uncertainty about the minimizer. We propose a novel criterion for global optimization and an associated sequential active learning strategy using Gaussian processes. Our criterion is the reduction of uncertainty… (More)

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Cite this paper

@article{Park2012ActiveBO, title={Active Bayesian Optimization: Minimizing Minimizer Entropy}, author={Il Memming Park and Marcel Nassar and Mijung Park}, journal={CoRR}, year={2012}, volume={abs/1202.2143} }