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arXiv · 2605.13302

Safe Bayesian Optimization for Uncertain Correlation Matrices in Linear Models of Co-Regionalization

Jannis Lübsen·Annika Eichler
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Abstract

This paper extends safety guarantees for multi-task Bayesian optimization with uncertain co-regionalization matrices from intrinsic co-regionalization models to linear models of co-regionalization. The latter allows for more flexible modeling of the inter-task correlations by composing multiple features. We derive uniform error bounds for vector-valued functions sampled from a Gaussian process with a linear model of co-regionalization kernel. Furthermore, we show the potential performance gains of linear models of co-regionalization in a numerical comparison on a safe multi-task Bayesian optimization benchmark.

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BibTeXRIS

Jannis Lübsen, Annika Eichler. 2026-05-13. Safe Bayesian Optimization for Uncertain Correlation Matrices in Linear Models of Co-Regionalization. https://arxiv.org/abs/2605.13302

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