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research article

Mutual information for low-rank even-order symmetric tensor estimation

Luneau, Clement  
•
Barbier, Jean  
•
Macris, Nicolas  
December 1, 2021
Information And Inference-A Journal Of The Ima

We consider a statistical model for finite-rank symmetric tensor factorization and prove a single-letter variational expression for its asymptotic mutual information when the tensor is of even order. The proof applies the adaptive interpolation method originally invented for rank-one factorization. Here we show how to extend the adaptive interpolation to finite-rank and even-order tensors. This requires new non-trivial ideas with respect to the current analysis in the literature. We also underline where the proof falls short when dealing with odd-order tensors.

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Type
research article
DOI
10.1093/imaiai/iaaa022
Web of Science ID

WOS:000743948700001

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

2021-12-01

Publisher

OXFORD UNIV PRESS

Published in
Information And Inference-A Journal Of The Ima
Volume

10

Issue

4

Start page

1167

End page

1207

Subjects

Mathematics, Applied

•

Mathematics

•

mutual information

•

tensor decomposition

•

adaptive interpolation method

•

concentration

•

replica formula

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LTHC  
Available on Infoscience
January 31, 2022
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/184905
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