Regret bounds for meta Bayesian optimization with an unknown Gaussian process prior

NeurIPS 2018 Zi WangBeomjoon KimLeslie Pack Kaelbling

Bayesian optimization usually assumes that a Bayesian prior is given. However, the strong theoretical guarantees in Bayesian optimization are often regrettably compromised in practice because of unknown parameters in the prior... (read more)

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