Works (2)

Updated: November 25th, 2024 07:13

2024 journal article

SMALL SINGULAR VALUES CAN INCREASE IN LOWER PRECISION\ast

SIAM JOURNAL ON MATRIX ANALYSIS AND APPLICATIONS, 45(3), 1518–1540.

By: C. Boutsikas*, P. Drineas* & I. Ipsen n

author keywords: singular values; eigenvalues; arithmetic precision; perturbation theory; real sym-
Sources: Web Of Science, ORCID, NC State University Libraries
Added: August 15, 2024

2019 journal article

LOW-RANK MATRIX APPROXIMATIONS DO NOT NEED A SINGULAR VALUE GAP

SIAM JOURNAL ON MATRIX ANALYSIS AND APPLICATIONS, 40(1), 299–319.

By: P. Drineas* & I. Ipsen n

Contributors: P. Drineas* & I. Ipsen n

author keywords: singular value decomposition; principal angles; additive perturbations; multiplicative perturbations
TL;DR: It is shown that the low-rank approximation errors, in the two-norm, Frobenius norm and more generally, any Schatten p- norm, are insensitive to additive rank-preserving perturbations in the projector basis; and to matrix perturbation that are additive or change the number of columns. (via Semantic Scholar)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: April 9, 2019

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