Sampling recovery of functions with mixed smoothness

Recently, a substantial progress in studying the problem of optimal sampling recovery was made in a number of papers. In particular, this resulted in some progress in studying sampling recovery on function classes with mixed smoothness. Mostly, the case of recovery in the square norm was studied. In...

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Detalhes bibliográficos
Autores: Kosov, Egor, Temlyakov, V. N.
Formato: artículo
Fecha de publicación:2025
País:España
Recursos:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:2072/484488
Acesso em linha:https://hdl.handle.net/2072/484488
Access Level:acceso abierto
Palavra-chave:Recovery
Universal sampling discretization
Sparse approximation
51
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spelling Sampling recovery of functions with mixed smoothness Kosov, Egor Temlyakov, V. N. Recovery Universal sampling discretization Sparse approximation 51 Recently, a substantial progress in studying the problem of optimal sampling recovery was made in a number of papers. In particular, this resulted in some progress in studying sampling recovery on function classes with mixed smoothness. Mostly, the case of recovery in the square norm was studied. In this paper we combine some of the new ideas developed recently in order to obtain progress in sampling recovery on classes with mixed smoothness in other integral norms. The research of E. D. Kosov was supported by the Marie Sklodowska-Curie grant 101109701, by PID2023-150984NB-I00 funded by MICIU/AEI/10.13039/501100011033/FEDER, EU, and by the Spanish State Research Agency, through the Severo Ochoa and Mar\u00EDa de Maeztu Program for Centers and Units of Excellence in R&D (CEX2020-001084-M). E. D. Kosov thanks CERCA Programme (Generalitat de Catalunya) for institutional support. The research of V. N. Temlyakov was carried out with the financial support of the Ministry of Science and Higher Education of the Russian Federation in the framework of a scientific project under agreement No. 075-15-2025-013. info:eu-repo/semantics/acceptedVersion Springer https://hdl.handle.net/2072/484488
title Sampling recovery of functions with mixed smoothness
spellingShingle Sampling recovery of functions with mixed smoothness
Kosov, Egor
Recovery
Universal sampling discretization
Sparse approximation
51
title_short Sampling recovery of functions with mixed smoothness
title_full Sampling recovery of functions with mixed smoothness
title_fullStr Sampling recovery of functions with mixed smoothness
title_full_unstemmed Sampling recovery of functions with mixed smoothness
title_sort Sampling recovery of functions with mixed smoothness
author Kosov, Egor
author_facet Kosov, Egor
Temlyakov, V. N.
author_role author
author2 Temlyakov, V. N.
author2_role author
topic Recovery
Universal sampling discretization
Sparse approximation
51
topic_facet Recovery
Universal sampling discretization
Sparse approximation
51
description Recently, a substantial progress in studying the problem of optimal sampling recovery was made in a number of papers. In particular, this resulted in some progress in studying sampling recovery on function classes with mixed smoothness. Mostly, the case of recovery in the square norm was studied. In this paper we combine some of the new ideas developed recently in order to obtain progress in sampling recovery on classes with mixed smoothness in other integral norms.
publishDate 2025
format article
url https://hdl.handle.net/2072/484488
eu_rights_str_mv openAccess
publisher Springer
institution Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
collection Recercat. Dipósit de la Recerca de Catalunya
reponame_str Recercat. Dipósit de la Recerca de Catalunya
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
_version_ 1878730878731943936
publishDateSort 2025
author_browse Kosov, Egor
Temlyakov, V. N.
publisherStr Springer
score 6,9008884