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product-of-experts

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papersTODAY 04:00 UTC

Bayesian Optimisation Method Combines Expert Gaussian Processes With Calibrated Uncertainty

A new arXiv preprint proposes using a product-of-experts Gaussian process as the surrogate model in Bayesian optimisation, rather than a single global GP. The authors address the cubic scaling cost of standard GP regression with training set size, which restricts its use on larger datasets, and add a calibration step for uncertainty estimates. The work falls in the machine learning methodology category and has not yet been peer reviewed.

bayesian-optimisation/gaussian-processes/uncertainty/arxiv