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Matrix compression along isogenic blocks

Lookup NU author(s): Professor Mihai Putinar

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

© 2022, The Author(s).A matrix-compression algorithm is derived from a novel isogenicblock decomposition for square matrices. The resulting compression andinflation operations possess strong functorial and spectral-permanenceproperties. The basic observation that Hadamard entrywise functionalcalculus preserves isogenic blocks has already proved to be of paramountimportance for thresholding large correlation matrices. The proposedisogenic stratification of the set of complex matrices bears similarities tothe Schubert cell stratification of a homogeneous algebraic manifold. Anarray of potential applications to current investigations in computationalmatrix analysis is briefly mentioned, touching concepts such as symmetricstatistical models, hierarchical matrices and coherent matrix organizationinduced by partition trees.


Publication metadata

Author(s): Belton A, Guillot D, Khare A, Putinar M

Publication type: Article

Publication status: Published

Journal: Acta Scientiarum Mathematicarum

Year: 2022

Volume: 88

Issue: 1-2

Pages: 417-448

Print publication date: 01/08/2022

Online publication date: 02/09/2022

Acceptance date: 18/03/2022

Date deposited: 24/02/2023

ISSN (print): 0001-6969

ISSN (electronic): 2064-8316

Publisher: Springer Nature

URL: https://doi.org/10.1007/s44146-022-00023-0

DOI: 10.1007/s44146-022-00023-0


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