Matrix perturbation bounds via contour bootstrapping

Fuente: arXiv
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Main Authors: Tran, Phuc, Vu, Van
Format: Preprint
Published: 2024
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author Tran, Phuc
Vu, Van
author_facet Tran, Phuc
Vu, Van
contents Matrix perturbation bounds play an essential role in the design and analysis of spectral algorithms. In this paper, we use a "contour bootstrapping" argument to derive several new perturbation bounds. As applications, we discuss new bounds on the error occurring when one uses matrix sparsification to speed up the computation of spectral parameters. Another potential application is the estimation of the trade-off in computing with privacy.
format Preprint
id arxiv_https___arxiv_org_abs_2407_05230
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Matrix perturbation bounds via contour bootstrapping
Tran, Phuc
Vu, Van
Numerical Analysis
Statistics Theory
68W40, 47A55
Matrix perturbation bounds play an essential role in the design and analysis of spectral algorithms. In this paper, we use a "contour bootstrapping" argument to derive several new perturbation bounds. As applications, we discuss new bounds on the error occurring when one uses matrix sparsification to speed up the computation of spectral parameters. Another potential application is the estimation of the trade-off in computing with privacy.
title Matrix perturbation bounds via contour bootstrapping
topic Numerical Analysis
Statistics Theory
68W40, 47A55
url https://arxiv.org/abs/2407.05230