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Simultanous search for all modes in multilinear models
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SYSNO ASEP 0341572 Document Type C - Proceedings Paper (int. conf.) R&D Document Type Conference Paper Title Simultanous search for all modes in multilinear models Author(s) Tichavský, Petr (UTIA-B) RID, ORCID
Koldovský, Zbyněk (UTIA-B) RIDSource Title Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing 2010. - Dallas : IEEE, 2010 - ISBN 978-1-4244-4296-6 Pages s. 4114-4117 Number of pages 4 s. Publication form www - www Action 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing Event date 14.03.2010-19.03.2010 VEvent location Dallas, TX Country US - United States Event type WRD Language eng - English Country US - United States Keywords tensor factorization ; multilinear models Subject RIV BB - Applied Statistics, Operational Research R&D Projects 1M0572 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) GA102/09/1278 GA ČR - Czech Science Foundation (CSF) CEZ AV0Z10750506 - UTIA-B (2005-2011) Annotation Parallel factor (PARAFAC) analysis is an extension of a low rank decomposition to higher way arrays, usually called tensors. Most of existing methods are based on an alternating least square (ALS) algorithm that proceeds iteratively, and minimizes a criterion (that is usually quadratic) of the fit with respect to individual factors one by one. Convergence of this approach is known to be slow, if some of the factor contain nearly co-linear vectors. This problem can be partly alleviated by an enhanced line search (ELS) by Rajih et al. (2008). In this paper we show that the method originally proposed by Paatero (1997), consisting in optimization with respect to all modes simultaneously, can be simplified, and can far outperform the ALS-ELS in ill--conditioned data in all modes. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2011
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