CANDECOMP/PARAFAC Decomposition of High-Order Tensors Through Tensor Reshaping
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F13%3A00396775" target="_blank" >RIV/67985556:_____/13:00396775 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/TSP.2013.2269046" target="_blank" >http://dx.doi.org/10.1109/TSP.2013.2269046</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TSP.2013.2269046" target="_blank" >10.1109/TSP.2013.2269046</a>
Alternative languages
Result language
angličtina
Original language name
CANDECOMP/PARAFAC Decomposition of High-Order Tensors Through Tensor Reshaping
Original language description
In general, algorithms for order-3 CANDECOMP/ PARAFAC (CP), also coined canonical polyadic decomposition (CPD), are easy to implement and can be extended to higher order CPD. Unfortunately, the algorithms become computationally demanding, and they are often not applicable to higher order and relatively large scale tensors. In this paper, by exploiting the uniqueness of CPD and the relation of a tensor in Kruskal form and its unfolded tensor, we propose a fast approach to deal with this problem. Insteadof directly factorizing the high order data tensor, the method decomposes an unfolded tensor with lower order, e.g., order-3 tensor. On the basis of the order-3 estimated tensor, a structured Kruskal tensor, of the same dimension as the data tensor, is then generated, and decomposed to find the final solution using fast algorithms for the structured CPD. In addition, strategies to unfold tensors are suggested and practically verified in the paper.
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
BB - Applied statistics, operational research
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GA102%2F09%2F1278" target="_blank" >GA102/09/1278: Advanced methods of blind source separation and blind deconvolution</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IEEE Transactions on Signal Processing
ISSN
1053-587X
e-ISSN
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Volume of the periodical
61
Issue of the periodical within the volume
19
Country of publishing house
US - UNITED STATES
Number of pages
14
Pages from-to
4847-4860
UT code for WoS article
000324342900017
EID of the result in the Scopus database
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