A sequential Monte Carlo approach to Thompson sampling for Bayesian optimization

1 Apr 2016Hildo BijlThomas B. SchönJan-Willem van WingerdenMichel Verhaegen

Bayesian optimization through Gaussian process regression is an effective method of optimizing an unknown function for which every measurement is expensive. It approximates the objective function and then recommends a new measurement point to try out... (read more)

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