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Main Authors: Garrido, Juan Guillermo, Pérez-Aros, Pedro, Vilches, Emilio
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2412.05952
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author Garrido, Juan Guillermo
Pérez-Aros, Pedro
Vilches, Emilio
author_facet Garrido, Juan Guillermo
Pérez-Aros, Pedro
Vilches, Emilio
contents This work investigates a dynamical system functioning as a nonsmooth adaptation of the continuous Newton method, aimed at minimizing the sum of a primal lower-regular and a locally Lipschitz function, both potentially nonsmooth. The classical Newton method's second-order information is extended by incorporating the graphical derivative of a locally Lipschitz mapping. Specifically, we analyze the existence and uniqueness of solutions, along with the asymptotic behavior of the system's trajectories. Conditions for convergence and respective convergence rates are established under two distinct scenarios: strong metric subregularity and satisfaction of the Kurdyka-Lojasiewicz inequality.
format Preprint
id arxiv_https___arxiv_org_abs_2412_05952
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A Newton-Like Dynamical System for Nonsmooth and Nonconvex Optimization
Garrido, Juan Guillermo
Pérez-Aros, Pedro
Vilches, Emilio
Optimization and Control
This work investigates a dynamical system functioning as a nonsmooth adaptation of the continuous Newton method, aimed at minimizing the sum of a primal lower-regular and a locally Lipschitz function, both potentially nonsmooth. The classical Newton method's second-order information is extended by incorporating the graphical derivative of a locally Lipschitz mapping. Specifically, we analyze the existence and uniqueness of solutions, along with the asymptotic behavior of the system's trajectories. Conditions for convergence and respective convergence rates are established under two distinct scenarios: strong metric subregularity and satisfaction of the Kurdyka-Lojasiewicz inequality.
title A Newton-Like Dynamical System for Nonsmooth and Nonconvex Optimization
topic Optimization and Control
url https://arxiv.org/abs/2412.05952