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  4. High-dimensional rank-one nonsymmetric matrix decomposition: the spherical case
 
conference paper

High-dimensional rank-one nonsymmetric matrix decomposition: the spherical case

Luneau, Clement  
•
Macris, Nicolas  
•
Barbier, Jean  
January 1, 2020
2020 Ieee International Symposium On Information Theory (Isit)
IEEE International Symposium on Information Theory (ISIT)

We consider the problem of estimating a rank-one nonsymmetric matrix under additive white Gaussian noise. The matrix to estimate can be written as the outer product of two vectors and we look at the special case in which both vectors are uniformly distributed on spheres. We prove a replica-symmetric formula for the average mutual information between these vectors and the observations in the high-dimensional regime. This goes beyond previous results which considered vectors with independent and identically distributed elements. The method used can be extended to rank-one tensor problems.

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Type
conference paper
DOI
10.1109/ISIT44484.2020.9174104
Web of Science ID

WOS:000714963402125

Author(s)
Luneau, Clement  
Macris, Nicolas  
Barbier, Jean  
Date Issued

2020-01-01

Publisher

IEEE

Publisher place

New York

Published in
2020 Ieee International Symposium On Information Theory (Isit)
ISBN of the book

978-1-7281-6432-8

Start page

2646

End page

2651

Subjects

matrix factorization

•

high-dimensional statistics

•

replica formula

•

tensor decompositions

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LTHC  
Event nameEvent placeEvent date
IEEE International Symposium on Information Theory (ISIT)

ELECTR NETWORK

Jun 21-26, 2020

Available on Infoscience
December 18, 2021
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/183882
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