3 papers
math.NA2025
Spectral equivalence of unsymmetric kernel matrices and applications
Tizian Wenzel, Armin Iske
Symmetric kernel matrices are a well-researched topic in the literature of kernel based approximation. In particular stability properties in terms of lower bounds on the smallest e…
cs.LG2024
Finetuning greedy kernel models by exchange algorithms
Tizian Wenzel, Armin Iske
Kernel based approximation offers versatile tools for high-dimensional approximation, which can especially be leveraged for surrogate modeling. For this purpose, both "knot inserti…
math.NA2024
A comparison study of supervised learning techniques for the approximation of high dimensional functions and feedback control
Mathias Oster, Luca Saluzzi, Tizian Wenzel
Approximation of high dimensional functions is in the focus of machine learning and data-based scientific computing. In many applications, empirical risk minimisation techniques ov…