Strengthened splitting methods for computing resolvents
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http://hdl.handle.net/10045/117430
Title: | Strengthened splitting methods for computing resolvents |
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Authors: | Aragón Artacho, Francisco Javier | Campoy, Rubén | Tam, Matthew K. |
Research Group/s: | Laboratorio de Optimización (LOPT) |
Center, Department or Service: | Universidad de Alicante. Departamento de Matemáticas |
Keywords: | Monotone operator | Resolvent | Splitting algorithm | Strengthening |
Knowledge Area: | Estadística e Investigación Operativa |
Issue Date: | 20-Aug-2021 |
Publisher: | Springer Nature |
Citation: | Computational Optimization and Applications. 2021, 80: 549-585. https://doi.org/10.1007/s10589-021-00291-6 |
Abstract: | In this work, we develop a systematic framework for computing the resolvent of the sum of two or more monotone operators which only activates each operator in the sum individually. The key tool in the development of this framework is the notion of the “strengthening” of a set-valued operator, which can be viewed as a type of regularisation that preserves computational tractability. After deriving a number of iterative schemes through this framework, we demonstrate their application to best approximation problems, image denoising and elliptic PDEs. |
Sponsor: | FJAA and RC were partially supported by the Ministry of Science, Innovation and Universities of Spain and the European Regional Development Fund (ERDF) of the European Commission, Grant PGC2018-097960-B-C22. MKT is supported in part by ARC grant DE200100063. |
URI: | http://hdl.handle.net/10045/117430 |
ISSN: | 0926-6003 (Print) | 1573-2894 (Online) |
DOI: | 10.1007/s10589-021-00291-6 |
Language: | eng |
Type: | info:eu-repo/semantics/article |
Rights: | © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 |
Peer Review: | si |
Publisher version: | https://doi.org/10.1007/s10589-021-00291-6 |
Appears in Collections: | INV - LOPT - Artículos de Revistas |
Files in This Item:
File | Description | Size | Format | |
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Aragon-Artacho_etal_2021_ComputOptimAppl_preprint.pdf | Preprint (acceso abierto) | 2,84 MB | Adobe PDF | Open Preview |
Aragon-Artacho_etal_2021_ComputOptimAppl_final.pdf | Versión final (acceso restringido) | 1,6 MB | Adobe PDF | Open Request a copy |
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