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SIAM Journal on Optimization
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Finite Convergence of Proximal-Gradient Inertial Algorithms Combining Dry Friction with Hessian-Driven Damping

Finite convergence of proximal-gradient inertial algorithms combining dry friction with Hessian-driven damping
descriptionPublicationkeyboard_double_arrow_right Article 01 Jan 2020 English Publisher:Society for Industrial & Applied Mathematics (SIAM)Journal:SIAM Journal on Optimization, volume 30, pages 2,134-2,162 (issn: 1052-6234, eissn: 1095-7189, Copyright policy )
Authors: Samir Adly; Hédy Attouch;

doi: 10.1137/19m1307779

Finite Convergence of Proximal-Gradient Inertial Algorithms Combining Dry Friction with Hessian-Driven Damping

Abstract

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Keywords

Evolution inclusions, finite convergence, Numerical solution to inverse problems in abstract spaces, inertial methods, Problems involving a system of particles with friction, Hessian-driven damping, proximal-gradient algorithms, differential inclusion, Lasso problem, Ordinary differential inclusions

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
26
Top 10%
Top 10%
Top 10%
bronze