82 citations · 433 across the 35 of their papers we have counts for
4 papers · 1 filter
Differentiable Kernel Ridge Regression for Deep Learning Pipelines
Jean-Marc Mercier, Gabriele Santin
Deep neural networks dominate modern machine learning, while alternative function approximators remain comparatively underexplored at scale. In this work, we revisit kernel methods…
Piecewise linear interpolation via kernels
Toni Karvonen, Gabriele Santin, Tizian Wenzel
We consider piecewise linear interpolation from the perspective of kernel interpolation and quadrature. If the Sobolev space is equipped with a suitable inner product…
Refined rates of convergence for target-data dependent greedy generalized interpolation with Sobolev kernels
Bernard Haasdonk, Gabriele Santin, Tizian Wenzel +1
Greedy methods have recently been successfully applied to generalized kernel interpolation, or the recovery of a function from data stemming from the evaluation of linear functiona…
On the optimal shape parameter for kernel methods: Sharp direct and inverse statements
Tizian Wenzel, Gabriele Santin
The search for the optimal shape parameter for Radial Basis Function (RBF) kernel approximation has been an outstanding research problem for decades. In this work, we establish a t…