Zobrazeno 1 - 10
of 38
pro vyhledávání: '"tensor rank decomposition"'
Autor:
Vannieuwenhoven, Nick 1
Publikováno v:
In Linear Algebra and Its Applications 15 December 2017 535:35-86
Autor:
Dennis Obster, Naoki Sasakura
Publikováno v:
Universe, Vol 7, Iss 8, p 302 (2021)
Tensor rank decomposition is a useful tool for geometric interpretation of the tensors in the canonical tensor model (CTM) of quantum gravity. In order to understand the stability of this interpretation, it is important to be able to estimate how man
Externí odkaz:
https://doaj.org/article/8018ac1cd9704533b682d09cbaad43a8
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Naoki Sasakura, Dennis Obster
Publikováno v:
Universe
Volume 7
Issue 8
Universe, Vol 7, Iss 302, p 302 (2021)
Volume 7
Issue 8
Universe, Vol 7, Iss 302, p 302 (2021)
The tensor rank decomposition is a useful tool for the geometric interpretation of the tensors in the canonical tensor model (CTM) of quantum gravity. In order to understand the stability of this interpretation, it is important to be able to estimate
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::06c83de0640c17a89f7216b1473e6229
Autor:
Shenglong Hu
Publikováno v:
Computational Optimization and Applications. 75:701-737
A strongly orthogonal decomposition of a tensor is a rank one tensor decomposition with the two component vectors in each mode of any two rank one tensors are either colinear or orthogonal. A strongly orthogonal decomposition with few number of rank
Publikováno v:
ICPR
In this paper11This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-000R22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledg
We propose a Riemannian conjugate gradient (CG) optimization method for finding low rank approximations of incomplete tensors. Our main contribution consists of an explicit expression of the geodesics on the Segre manifold. These are exploited in our
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e1b1ac2f7bf0fb2c7c01714a74f12524
Publikováno v:
SIAM J. MATRIX ANAL. APPL.Vol. 40, No. 2, pp. 739–773
SIAM Journal on Matrix Analysis and Applications
UCrea Repositorio Abierto de la Universidad de Cantabria
Universidad de Cantabria (UC)
SIAM Journal on Matrix Analysis and Applications
UCrea Repositorio Abierto de la Universidad de Cantabria
Universidad de Cantabria (UC)
We prove the existence of an open set of $n_1\times n_2 \times n_3$ tensors of rank $r$ on which a popular and efficient class of algorithms for computing tensor rank decompositions based on a reduction to a linear matrix pencil, typically followed b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a256ac784b702c7ff73cdb85067baca7
http://hdl.handle.net/10902/18159
http://hdl.handle.net/10902/18159
Autor:
Paul Breiding, Nick Vannieuwenhoven
The join set of a finite collection of smooth embedded submanifolds of a mutual vector space is defined as their Minkowski sum. Join decompositions generalize some ubiquitous decompositions in multilinear algebra, namely tensor rank, Waring, partiall
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c90c184abef41ce4a8bca53d9931e5db
https://lirias.kuleuven.be/handle/123456789/599573
https://lirias.kuleuven.be/handle/123456789/599573