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Speeding up PARAFAC: Approximation of tensor rank using the Tucker core
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
2018 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

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.

Place, publisher, year, edition, pages
2018. , p. 34
Keywords [en]
Tucker decomposition, PARAFAC, tensor rank, split-half analysis
National Category
Probability Theory and Statistics Other Mathematics
Identifiers
URN: urn:nbn:se:uu:diva-353287OAI: oai:DiVA.org:uu-353287DiVA, id: diva2:1216742
Subject / course
Statistics
Educational program
Master Programme in Statistics
Supervisors
Examiners
Available from: 2018-06-19 Created: 2018-06-12 Last updated: 2018-06-19Bibliographically approved

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SpeedingUpPARAFAC(3006 kB)48 downloads
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Probability Theory and StatisticsOther Mathematics

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf