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

ArXi:2605.13302v1 Announce Type: new This paper extends safety guarantees for multi-task Bayesian optimization with uncertain correlation matrices from intrinsic co-reginalization models to linear models of co-reginalization. The latter allows for 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-reginalization kernel.