Showing math.NAShow all
3 papers · 1 filter
math.NA2026
Samplet compression for conditionally positive definite kernels and universal Kriging
Sara Avesani, Rüdiger Kempf, Michael Multerer +1
We present a samplet-based framework for the efficient numerical solution of saddle-point systems arising from conditionally positive definite (CPD) kernel approximation in general…
math.NA2026
Data-intrinsic approximation in metric spaces
Jürgen Dölz, Michael Multerer
Analysis and processing of data is a vital part of our modern society and requires vast amounts of computational resources. To reduce the computational burden, compressing and appr…
math.NA2024
On Quasi-Localized Dual Pairs in Reproducing Kernel Hilbert Spaces
Helmut Harbrecht, Rüdiger Kempf, Michael Multerer
In scattered data approximation, the span of a finite number of translates of a chosen radial basis function is used as approximation space and the basis of translates is used for…