Počet záznamů: 1
Partitioned Alternating Least Squares Technique for Canonical Polyadic Tensor Decomposition
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SYSNO ASEP 0460710 Druh ASEP J - Článek v odborném periodiku Zařazení RIV J - Článek v odborném periodiku Poddruh J Článek ve WOS Název Partitioned Alternating Least Squares Technique for Canonical Polyadic Tensor Decomposition Tvůrce(i) Tichavský, Petr (UTIA-B) RID, ORCID
Phan, A. H. (JP)
Cichocki, A. (JP)Celkový počet autorů 3 Zdroj.dok. IEEE Signal Processing Letters. - : Institute of Electrical and Electronics Engineers - ISSN 1070-9908
Roč. 23, č. 7 (2016), s. 993-997Poč.str. 5 s. Forma vydání Tištěná - P Jazyk dok. eng - angličtina Země vyd. US - Spojené státy americké Klíč. slova canonical polyadic decomposition ; PARAFAC ; tensor decomposition Vědní obor RIV BB - Aplikovaná statistika, operační výzkum CEP GA14-13713S GA ČR - Grantová agentura ČR Institucionální podpora UTIA-B - RVO:67985556 UT WOS 000379694800005 EID SCOPUS 84978100769 DOI 10.1109/LSP.2016.2577383 Anotace Canonical polyadic decomposition (CPD), also known as parallel factor analysis, is a representation of a given tensor as a sum of rank-one components. Traditional method for accomplishing CPD is the alternating least squares (ALS) algorithm. Convergence of ALS is known to be slow, especially when some factor matrices of the tensor contain nearly collinear columns. We propose a novel variant of this technique, in which the factor matrices are partitioned into blocks, and each iteration jointly updates blocks of different factor matrices. Each partial optimization is quadratic and can be done in closed form. The algorithm alternates between different random partitionings of the matrices. As a result, a faster convergence is achieved. Another improvement can be obtained when the method is combined with the enhanced line search of Rajih et al. Complexity per iteration is between those of the ALS and the Levenberg–Marquardt (damped Gauss–Newton) method. Pracoviště Ústav teorie informace a automatizace Kontakt Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Rok sběru 2017
Počet záznamů: 1