Numerical CP Decomposition of Some Difficult Tensors

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F17%3A00468385" target="_blank" >RIV/67985556:_____/17:00468385 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.cam.2016.12.007" target="_blank" >http://dx.doi.org/10.1016/j.cam.2016.12.007</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.cam.2016.12.007" target="_blank" >10.1016/j.cam.2016.12.007</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Numerical CP Decomposition of Some Difficult Tensors

Popis výsledku v původním jazyce

In this paper, a numerical method is proposed for canonical polyadic (CP) decomposition of small size tensors. The focus is primarily on decomposition of tensors that correspond to small matrix multiplications. Here, rank of the tensors is equal to the smallest number of scalar multiplications that are necessary to accomplish the matrix multiplication. The proposed method is based on a constrained Levenberg-Marquardt optimization. Numerical results indicate the rank and border ranks of tensors that correspond to multiplication of matrices of the size 2x3 and 3x2, 3x3 and 3x2,n3x3 and 3x3, and 3x4 and 4x3. The ranks are 11, 15, 23 and 29, respectively. In particular, a novel algorithm for computing product of matrices of the sizes 3x4 and 4x3 using 29 multiplications is presented.

Název v anglickém jazyce

Numerical CP Decomposition of Some Difficult Tensors

Popis výsledku anglicky

In this paper, a numerical method is proposed for canonical polyadic (CP) decomposition of small size tensors. The focus is primarily on decomposition of tensors that correspond to small matrix multiplications. Here, rank of the tensors is equal to the smallest number of scalar multiplications that are necessary to accomplish the matrix multiplication. The proposed method is based on a constrained Levenberg-Marquardt optimization. Numerical results indicate the rank and border ranks of tensors that correspond to multiplication of matrices of the size 2x3 and 3x2, 3x3 and 3x2,n3x3 and 3x3, and 3x4 and 4x3. The ranks are 11, 15, 23 and 29, respectively. In particular, a novel algorithm for computing product of matrices of the sizes 3x4 and 4x3 using 29 multiplications is presented.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10102 - Applied mathematics

Projekt

<a href="/cs/project/GA14-13713S" target="_blank" >GA14-13713S: Metody dekompozice tenzorů a jejich aplikace</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of Computational and Applied Mathematics

ISSN

0377-0427

e-ISSN

—

Svazek periodika

317

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

9

Strana od-do

362-370

Kód UT WoS článku

000394628800024

EID výsledku v databázi Scopus

2-s2.0-85007372598