Kernel-based Approximation Methods using MATLAB

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Hyper-Parameter Optimization: A Review of Algorithms and Applications (2020, background): “…in various ways, and thus two or more kernels can be used simultaneously for GP. Prediction following a normal distribution p(y|x,D) = N(y|µ̂, σ̂2) (Fasshauer and McCourt, 2015) with µ0(x) = 0 has a posterior distribution of µn(x) = k(x) T (K + σ2I)−1y σ2n(x) = k(x, x)− k(x)T (K +…”
Bayesian Optimization over Sets (2019, background): “…the covariance between elements in X {{ This belief is imposed in the form of a positive-deﬁnite covariance kernel k set : X set × X set → R ; see [25, 5] for more discussion on approximation with kernels. the symmetry In addition to k set ( X ( i ) , X ( j ) ) = k set ( X ( j ) , X ( i ) )…”