About: Stability Analysis and Fast Damped-Gauss-Newton Algorithm for INDSCALTensor Decomposition

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	INDSCAL is a special case of the CANDECOMP-PARAFAC (CP) decomposition of three or more-way tensors, where two factor matrices are equal. This paper provides a stability analysis of INDSCAL that is done by deriving the Cram'er-Rao lower bound (CRLB) on variance of an unbiased estimate of the tensor parameters from its noisy observation (the tensor plus a Gaussian random tensor). The existence of the bound reveals necessary conditions for the essential uniqueness of the INDSCAL decomposition. This is compared with previous results on CP. Next, analytical expressions for the inverse of the Hessian matrix, which is needed to compute the CRLB, are used in a damped Gaussian (Levenberg-Marquardt) algorithm, which gives a novel method for INDSCAL having a lower computational complexity. INDSCAL is a special case of the CANDECOMP-PARAFAC (CP) decomposition of three or more-way tensors, where two factor matrices are equal. This paper provides a stability analysis of INDSCAL that is done by deriving the Cram'er-Rao lower bound (CRLB) on variance of an unbiased estimate of the tensor parameters from its noisy observation (the tensor plus a Gaussian random tensor). The existence of the bound reveals necessary conditions for the essential uniqueness of the INDSCAL decomposition. This is compared with previous results on CP. Next, analytical expressions for the inverse of the Hessian matrix, which is needed to compute the CRLB, are used in a damped Gaussian (Levenberg-Marquardt) algorithm, which gives a novel method for INDSCAL having a lower computational complexity. (en)
Title	Stability Analysis and Fast Damped-Gauss-Newton Algorithm for INDSCALTensor Decomposition Stability Analysis and Fast Damped-Gauss-Newton Algorithm for INDSCALTensor Decomposition (en)
skos:prefLabel	Stability Analysis and Fast Damped-Gauss-Newton Algorithm for INDSCALTensor Decomposition Stability Analysis and Fast Damped-Gauss-Newton Algorithm for INDSCALTensor Decomposition (en)
skos:notation	RIV/67985556:_____/11:00363806!RIV12-AV0-67985556
http://linked.open...avai/riv/aktivita	P Z
http://linked.open...avai/riv/aktivity	P(1M0572), P(GA102/09/1278), Z(AV0Z10750506)
http://linked.open...vai/riv/dodaniDat	2012
http://linked.open...aciTvurceVysledku	Tichavský, Petr Koldovský, Zbyněk
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Ústav teorie informace a automatizace AV ČR, v. v. i.
http://linked.open...dnocenehoVysledku	231836
http://linked.open...ai/riv/idVysledku	RIV/67985556:_____/11:00363806
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	INDSCAL; PARAFAC; tensor decomposition (en)
http://linked.open.../riv/klicoveSlovo	INDSCAL PARAFAC tensor decomposition
http://linked.open...ontrolniKodProRIV	[3090987D6C75]
http://linked.open...v/mistoKonaniAkce	Nice
http://linked.open...i/riv/mistoVydani	Nice
http://linked.open...i/riv/nazevZdroje	2011 IEEE Statistical Signal Processing Workshop (SSP) Proceedings
http://linked.open...in/vavai/riv/obor	BB
http://linked.open...ichTvurcuVysledku	2 (xsd:int)
http://linked.open...cetTvurcuVysledku	3 (xsd:int)
http://linked.open...vavai/riv/projekt	Advanced methods of blind source separation and blind deconvolution Data, algorithms, decision making
http://linked.open...UplatneniVysledku	2011
http://linked.open...iv/tvurceVysledku	Koldovský, Zbyněk Tichavský, Petr Phan, A. H.
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2011-06-28 (xsd:date)
http://linked.open...n/vavai/riv/zamer	Pokročilé matematické metody získávání, zpracování a využití informací a znalostí ve složitých a nedeterministických systémech
number of pages	4 (xsd:int)
http://purl.org/ne...btex#hasPublisher	IEEE Signal Processing Society
https://schema.org/isbn	978-1-4577-0569-4

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