productkernelconstructies
Product kernel constructions refer to building kernel functions by taking the product of simpler base kernels defined on individual input components or feature blocks. For an input x partitioned into blocks x = (x1, x2, ..., xK) and kernels ki on each block, a product kernel is k(x, x') = ∏i ki(xi, x'i). This operation preserves positive semidefiniteness: the product of PSD kernels is PSD, so k is a valid kernel. Product kernels enable modeling of interactions across modalities or feature groups without enumerating all cross terms.
In practice, product kernels are used to define covariance structures in Gaussian processes and to construct
Computationally, the kernel matrix under a product kernel can sometimes be exploited via Kronecker or low-rank
See also: kernel methods, reproducing kernel Hilbert space, Gaussian processes, Kronecker product, multi-view learning.