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Bayesian Optimistic Optimisation with Exponentially Decaying Regret

ICML 2021 · Probabilistic and scientific modeling › Bayesian optimization · approach: Regret bounds for Bayesian optimization · 0 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use BOO instead of the compared baselinesSynthetic function optimisation · Hartmann3, Schwefel, and Shekellog distance to true optimumMixed
Use BOO instead of the compared baselinesElastic Net hyperparameter tuning · MNISTlog prediction errorHelped
Use BOO instead of the compared baselinesMLP hyperparameter tuning · MNISTlog prediction errorHelped
Use BOO instead of the compared baselinesXGBoost hyperparameter tuning · Skin Segmentationclassification prediction errorHelped
Use BOO rather than GP-EI or GP-UCBSynthetic function optimisation · Hartmann, Shekel, and SchwefelCPU time (seconds)Helped
Use BOO rather than SOOSynthetic function optimisation · Hartmann, Shekel, and SchwefelCPU time (seconds)Hurt

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