Empirical Analysis of Stochastic Methods of Linear Algebra

In this paper we present the results of an empirical study of stochastic projection and stochastic gradient descent methods as means of obtaining approximate inverses and preconditioners for iterative methods. Results of numerical experiments are used to analyse scalability and overall suitability o...

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Detalles Bibliográficos
Autores principales: Şahin, Mustafa Emre, Lebedev, Anton, Alexandrov, Vassil
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7304785/
http://dx.doi.org/10.1007/978-3-030-50436-6_40
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author Şahin, Mustafa Emre
Lebedev, Anton
Alexandrov, Vassil
author_facet Şahin, Mustafa Emre
Lebedev, Anton
Alexandrov, Vassil
author_sort Şahin, Mustafa Emre
collection PubMed
description In this paper we present the results of an empirical study of stochastic projection and stochastic gradient descent methods as means of obtaining approximate inverses and preconditioners for iterative methods. Results of numerical experiments are used to analyse scalability and overall suitability of the selected methods as practical tools for treatment of large linear systems of equations. The results are preliminary due to the code being not yet fully optimized.
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spelling pubmed-73047852020-06-22 Empirical Analysis of Stochastic Methods of Linear Algebra Şahin, Mustafa Emre Lebedev, Anton Alexandrov, Vassil Computational Science – ICCS 2020 Article In this paper we present the results of an empirical study of stochastic projection and stochastic gradient descent methods as means of obtaining approximate inverses and preconditioners for iterative methods. Results of numerical experiments are used to analyse scalability and overall suitability of the selected methods as practical tools for treatment of large linear systems of equations. The results are preliminary due to the code being not yet fully optimized. 2020-05-25 /pmc/articles/PMC7304785/ http://dx.doi.org/10.1007/978-3-030-50436-6_40 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Şahin, Mustafa Emre
Lebedev, Anton
Alexandrov, Vassil
Empirical Analysis of Stochastic Methods of Linear Algebra
title Empirical Analysis of Stochastic Methods of Linear Algebra
title_full Empirical Analysis of Stochastic Methods of Linear Algebra
title_fullStr Empirical Analysis of Stochastic Methods of Linear Algebra
title_full_unstemmed Empirical Analysis of Stochastic Methods of Linear Algebra
title_short Empirical Analysis of Stochastic Methods of Linear Algebra
title_sort empirical analysis of stochastic methods of linear algebra
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7304785/
http://dx.doi.org/10.1007/978-3-030-50436-6_40
work_keys_str_mv AT sahinmustafaemre empiricalanalysisofstochasticmethodsoflinearalgebra
AT lebedevanton empiricalanalysisofstochasticmethodsoflinearalgebra
AT alexandrovvassil empiricalanalysisofstochasticmethodsoflinearalgebra

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