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Lookup NU author(s): Professor Mihai Putinar
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 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.
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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