Construction of multivariate polynomial approximation kernels via semidefinite programming

In this paper we construct a hierarchy of multivariate polynomial approximation kernels via semidefinite programming. We give details on the implementation of the semidefinite programs defining the kernels. Finally, we show how a symmetry reduction may be performed to increase numerical tractability...

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Veröffentlicht in:arXiv.org
Hauptverfasser: Kirschner, Felix, Etienne de Klerk
Format: Paper
Sprache:Englisch
Veröffentlicht: Ithaca Cornell University Library, arXiv.org 17.07.2023
Schlagworte:
Approximation
Kernels
Mathematical analysis
Multivariate analysis
Polynomials
Semidefinite programming
ISSN:2331-8422
Online-Zugang:Volltext
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Zusammenfassung:In this paper we construct a hierarchy of multivariate polynomial approximation kernels via semidefinite programming. We give details on the implementation of the semidefinite programs defining the kernels. Finally, we show how a symmetry reduction may be performed to increase numerical tractability.
Bibliographie:content type line 50
SourceType-Working Papers-1
ObjectType-Working Paper/Pre-Print-1
ISSN:2331-8422