3 papers
stat.ML2025
Uniform convergence for Gaussian kernel ridge regression
Paul Dommel, Rajmadan Lakshmanan
This paper establishes the first polynomial convergence rates for Gaussian kernel ridge regression (KRR) with a fixed hyperparameter in both the uniform and the -norm. The u…
stat.ML2025
A Bound on the Maximal Marginal Degrees of Freedom
Paul Dommel
Kernel ridge regression, in general, is expensive in memory allocation and computation time. This paper addresses low rank approximations and surrogates for kernel ridge regression…
stat.ML2024
On the Approximation of Kernel functions
Paul Dommel, Alois Pichler
Various methods in statistical learning build on kernels considered in reproducing kernel Hilbert spaces. In applications, the kernel is often selected based on characteristics of…