A Beta-distribution-based kernel gives Gaussian process optimizers higher prior variance near the boundaries of a unit box, improving Bayesian optimization when optima lie near faces or vertices, including on model compression tasks.
Handbook of mathematical functions with formulas, graphs, and mathematical tables, volume 55
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Bayesian Optimization over Bounded Domains with the Beta Product Kernel
A Beta-distribution-based kernel gives Gaussian process optimizers higher prior variance near the boundaries of a unit box, improving Bayesian optimization when optima lie near faces or vertices, including on model compression tasks.