Optimization, fast and slow: optimally switching between local and Bayesian optimization

We develop the first Bayesian Optimization algorithm, BLOSSOM, which selects between multiple alternative acquisition functions and traditional local optimization at each step. This is combined with a novel stopping condition based on expected regret... (read more)

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