A geodesic convexity-like structure for the polar decomposition of a square matrix

Fuente: arXiv
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Main Authors: Alimisis, Foivos, Vandereycken, Bart
Format: Preprint
Published: 2024
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author Alimisis, Foivos
Vandereycken, Bart
author_facet Alimisis, Foivos
Vandereycken, Bart
contents We make a full landscape analysis of the (generally non-convex) orthogonal Procrustes problem. This problem is equivalent to computing the polar factor of a square matrix. We reveal a convexity-like structure, which explains the already established tractability of the problem and show that gradient descent in the orthogonal group computes the polar factor of a square matrix with linear convergence rate if the matrix is invertible and with an algebraic one if the matrix is singular. These results are similar to the ones of Alimisis and Vandereycken (2024) for the symmetric eigenvalue problem.
format Preprint
id arxiv_https___arxiv_org_abs_2412_13990
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A geodesic convexity-like structure for the polar decomposition of a square matrix
Alimisis, Foivos
Vandereycken, Bart
Numerical Analysis
Optimization and Control
We make a full landscape analysis of the (generally non-convex) orthogonal Procrustes problem. This problem is equivalent to computing the polar factor of a square matrix. We reveal a convexity-like structure, which explains the already established tractability of the problem and show that gradient descent in the orthogonal group computes the polar factor of a square matrix with linear convergence rate if the matrix is invertible and with an algebraic one if the matrix is singular. These results are similar to the ones of Alimisis and Vandereycken (2024) for the symmetric eigenvalue problem.
title A geodesic convexity-like structure for the polar decomposition of a square matrix
topic Numerical Analysis
Optimization and Control
url https://arxiv.org/abs/2412.13990