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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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 |
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English |
format |
Others
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Tucker decomposition PARAFAC tensor rank split-half analysis Probability Theory and Statistics Sannolikhetsteori och statistik Other Mathematics Annan matematik |
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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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1718697889703657472 |