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Article: Sufficient Conditions for Instability of the Subgradient Method with Constant Step Size

TitleSufficient Conditions for Instability of the Subgradient Method with Constant Step Size
Authors
Issue Date31-Mar-2024
Citation
SIAM Journal on Optimization, 2024, v. 34, n. 1 How to Cite?
Abstract

We provide sufficient conditions for instability of the subgradient method with constant step size around a local minimum of a locally Lipschitz semialgebraic function. They are satisfied by several spurious local minima arising in robust principal component analysis and neural networks.


Persistent Identifierhttp://hdl.handle.net/10722/356003
ISSN
2023 Impact Factor: 2.6
2023 SCImago Journal Rankings: 2.138
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorJosz, Cédric-
dc.contributor.authorLai, Lexiao-
dc.date.accessioned2025-05-21T00:35:13Z-
dc.date.available2025-05-21T00:35:13Z-
dc.date.issued2024-03-31-
dc.identifier.citationSIAM Journal on Optimization, 2024, v. 34, n. 1-
dc.identifier.issn1052-6234-
dc.identifier.urihttp://hdl.handle.net/10722/356003-
dc.description.abstract<p>We provide sufficient conditions for instability of the subgradient method with constant step size around a local minimum of a locally Lipschitz semialgebraic function. They are satisfied by several spurious local minima arising in robust principal component analysis and neural networks.<br></p>-
dc.languageeng-
dc.relation.ispartofSIAM Journal on Optimization-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.titleSufficient Conditions for Instability of the Subgradient Method with Constant Step Size-
dc.typeArticle-
dc.identifier.doi10.1137/22m1535723-
dc.identifier.volume34-
dc.identifier.issue1-
dc.identifier.eissn1095-7189-
dc.identifier.isiWOS:001174991600013-
dc.identifier.issnl1052-6234-

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