OSCBO adaptively balances Gaussian process sharpness and calibration in Bayesian optimization by casting hyperparameter selection as constrained online learning, while preserving sublinear regret bounds.
Regret bounds for meta Bayesian optimization with an unknown Gaussian process prior.Advances in Neural Information Processing Systems
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Online Sharp-Calibrated Bayesian Optimization
OSCBO adaptively balances Gaussian process sharpness and calibration in Bayesian optimization by casting hyperparameter selection as constrained online learning, while preserving sublinear regret bounds.