Construction of multivariate polynomial approximation kernels via semidefinite programming
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| Název: | Construction of multivariate polynomial approximation kernels via semidefinite programming |
|---|---|
| Autoři: | Kirschner, Felix, de Klerk, Etienne |
| Zdroj: | SIAM Journal on Optimization vol.33 (2023) nr.2 p.513 - 537 [ISSN 1052-6234] |
| Informace o vydavateli: | 2023 |
| Druh dokumentu: | Electronic Resource |
| Abstrakt: | In this paper we construct a hierarchy of multivariate polynomial approximation kernels for uniformly continuous functions on the hypercube via semidefinite programming. We give details on the implementation of the semidefinite programs defining the kernels. Finally, we show how symmetry reduction may be performed to increase numerical tractability. |
| Témata: | polynomial kernel method, semidefinite programming, symmetry reduction, Article |
| URL: | |
| Dostupnost: | Open access content. Open access content info:eu-repo/semantics/openAccess (c) Universiteit van Tilburg |
| Poznámka: | DOI: 10.1137/22M1494476 SIAM Journal on Optimization vol.33 (2023) nr.2 p.513 - 537 [ISSN 1052-6234] English |
| Other Numbers: | GRG oai:tilburguniversity.edu:publications/9b1d01ec-074f-404f-a8d0-6abdc7f0b127 https://research.tilburguniversity.edu/en/publications/9b1d01ec-074f-404f-a8d0-6abdc7f0b127 1393132913 |
| Přispívající zdroj: | TILBURG UNIV From OAIster®, provided by the OCLC Cooperative. |
| Přístupové číslo: | edsoai.on1393132913 |
| Databáze: | OAIster |
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