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Bibliographic Details
Main Authors: Gnewuch, Michael, Kritzer, Peter, Ritter, Klaus
Format: Preprint
Published: 2026
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Online Access:https://arxiv.org/abs/2604.27160
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author Gnewuch, Michael
Kritzer, Peter
Ritter, Klaus
author_facet Gnewuch, Michael
Kritzer, Peter
Ritter, Klaus
contents We study embeddings between reproducing kernel Hilbert spaces $H(K)$ of functions of $d \in \mathbb{N} \cup \{\infty\}$ variables. The kernels $K$ are superpositions of weighted finite tensor products of a fixed univariate kernel. The basic idea for the embeddings is to compensate a change of the univariate kernel by a suitable transformation of the weights. For the proofs we employ ($d \in \mathbb{N}$) and develop ($d = \infty$) a discrete calculus on the cone of all weights, where completely monotone weights play a particular role. We sketch how to apply the embedding results to computational problems, as, e.g., numerical integration or function recovery.
format Preprint
id arxiv_https___arxiv_org_abs_2604_27160
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Embeddings of Reproducing Kernel Hilbert Spaces with General Weights
Gnewuch, Michael
Kritzer, Peter
Ritter, Klaus
Numerical Analysis
We study embeddings between reproducing kernel Hilbert spaces $H(K)$ of functions of $d \in \mathbb{N} \cup \{\infty\}$ variables. The kernels $K$ are superpositions of weighted finite tensor products of a fixed univariate kernel. The basic idea for the embeddings is to compensate a change of the univariate kernel by a suitable transformation of the weights. For the proofs we employ ($d \in \mathbb{N}$) and develop ($d = \infty$) a discrete calculus on the cone of all weights, where completely monotone weights play a particular role. We sketch how to apply the embedding results to computational problems, as, e.g., numerical integration or function recovery.
title Embeddings of Reproducing Kernel Hilbert Spaces with General Weights
topic Numerical Analysis
url https://arxiv.org/abs/2604.27160