Inexact Newton Methods for Solving Generalized Equations on Riemannian Manifolds

Fuente: arXiv
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Main Authors: Louzeiro, Mauricio S., Silva, Gilson N., Yuan, Jinyun, Zhang, Daoping
Format: Preprint
Published: 2023
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author Louzeiro, Mauricio S.
Silva, Gilson N.
Yuan, Jinyun
Zhang, Daoping
author_facet Louzeiro, Mauricio S.
Silva, Gilson N.
Yuan, Jinyun
Zhang, Daoping
contents The convergence of inexact Newton methods is studied for solving generalized equations on Riemannian manifolds by using the metric regularity property, which is also explored. Under appropriate conditions and without any additional geometric assumptions, local convergence results with linear and quadratic rates, as well as a semi-local convergence result, are obtained for the proposed method. Finally, the theory is applied to the problem of finding a singularity for the sum of two vector fields. In particular, the KKT system for the constrained Riemannian center of mass on the sphere is explored numerically.
format Preprint
id arxiv_https___arxiv_org_abs_2303_10554
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Inexact Newton Methods for Solving Generalized Equations on Riemannian Manifolds
Louzeiro, Mauricio S.
Silva, Gilson N.
Yuan, Jinyun
Zhang, Daoping
Numerical Analysis
Optimization and Control
The convergence of inexact Newton methods is studied for solving generalized equations on Riemannian manifolds by using the metric regularity property, which is also explored. Under appropriate conditions and without any additional geometric assumptions, local convergence results with linear and quadratic rates, as well as a semi-local convergence result, are obtained for the proposed method. Finally, the theory is applied to the problem of finding a singularity for the sum of two vector fields. In particular, the KKT system for the constrained Riemannian center of mass on the sphere is explored numerically.
title Inexact Newton Methods for Solving Generalized Equations on Riemannian Manifolds
topic Numerical Analysis
Optimization and Control
url https://arxiv.org/abs/2303.10554