Speeding up PARAFAC : Approximation of tensor rank using the Tucker core

In this paper, the approach of utilizing the core tensor from the Tucker decomposition, in place of theuncompressed tensor, for nding a valid tensor rank for the PARAFAC decomposition is considered.Validity of the proposed method is investigated in terms of error and time consumption. As thesolution...

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Main Author: Arnroth, Lukas
Format: Others
Language:English
Published: Uppsala universitet, Statistiska institutionen 2018
Subjects:
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-353287
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spelling ndltd-UPSALLA1-oai-DiVA.org-uu-3532872018-06-20T05:56:29ZSpeeding up PARAFAC : Approximation of tensor rank using the Tucker coreengArnroth, LukasUppsala universitet, Statistiska institutionen2018Tucker decompositionPARAFACtensor ranksplit-half analysisProbability Theory and StatisticsSannolikhetsteori och statistikOther MathematicsAnnan matematikIn this paper, the approach of utilizing the core tensor from the Tucker decomposition, in place of theuncompressed tensor, for nding a valid tensor rank for the PARAFAC decomposition is considered.Validity of the proposed method is investigated in terms of error and time consumption. As thesolutions of the PARAFAC decomposition are unique, stability of the solutions through split-halfanalysis is investigated. Simulated and real data are considered. Although, no general validity ofthe method could be observed, the results for some datasets look promising with 10% compressionin all modes. It is also shown that increased compression does not necessarily imply less timeconsumption. Student thesisinfo:eu-repo/semantics/bachelorThesistexthttp://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-353287application/pdfinfo:eu-repo/semantics/openAccess
collection NDLTD
language English
format Others
sources NDLTD
topic Tucker decomposition
PARAFAC
tensor rank
split-half analysis
Probability Theory and Statistics
Sannolikhetsteori och statistik
Other Mathematics
Annan matematik
spellingShingle Tucker decomposition
PARAFAC
tensor rank
split-half analysis
Probability Theory and Statistics
Sannolikhetsteori och statistik
Other Mathematics
Annan matematik
Arnroth, Lukas
Speeding up PARAFAC : Approximation of tensor rank using the Tucker core
description In this paper, the approach of utilizing the core tensor from the Tucker decomposition, in place of theuncompressed tensor, for nding a valid tensor rank for the PARAFAC decomposition is considered.Validity of the proposed method is investigated in terms of error and time consumption. As thesolutions of the PARAFAC decomposition are unique, stability of the solutions through split-halfanalysis is investigated. Simulated and real data are considered. Although, no general validity ofthe method could be observed, the results for some datasets look promising with 10% compressionin all modes. It is also shown that increased compression does not necessarily imply less timeconsumption.
author Arnroth, Lukas
author_facet Arnroth, Lukas
author_sort Arnroth, Lukas
title Speeding up PARAFAC : Approximation of tensor rank using the Tucker core
title_short Speeding up PARAFAC : Approximation of tensor rank using the Tucker core
title_full Speeding up PARAFAC : Approximation of tensor rank using the Tucker core
title_fullStr Speeding up PARAFAC : Approximation of tensor rank using the Tucker core
title_full_unstemmed Speeding up PARAFAC : Approximation of tensor rank using the Tucker core
title_sort speeding up parafac : approximation of tensor rank using the tucker core
publisher Uppsala universitet, Statistiska institutionen
publishDate 2018
url http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-353287
work_keys_str_mv AT arnrothlukas speedingupparafacapproximationoftensorrankusingthetuckercore
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