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On Batch Bayesian Optimization (1911.01032v1)
Published 4 Nov 2019 in cs.LG and stat.ML
Abstract: We present two algorithms for Bayesian optimization in the batch feedback setting, based on Gaussian process upper confidence bound and Thompson sampling approaches, along with frequentist regret guarantees and numerical results.
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