2 papers
math.NA2025
An approach to discrete operator learning based on sparse high-dimensional approximation
Daniel Potts, Fabian Taubert
We present a dimension-incremental method for function approximation in bounded orthonormal product bases to learn the solutions of various differential equations. Therefore, we de…
cs.LG2024
Fast and interpretable Support Vector Classification based on the truncated ANOVA decomposition
Kseniya Akhalaya, Franziska Nestler, Daniel Potts
Support Vector Machines (SVMs) are an important tool for performing classification on scattered data, where one usually has to deal with many data points in high-dimensional spaces…