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  Scalable Robust Principal Component Analysis using Grassmann Averages

Hauberg, S., Feragen, A., Enficiaud, R., & Black, M. J. (2016). Scalable Robust Principal Component Analysis using Grassmann Averages. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(11), 2298-2311. doi:10.1109/TPAMI.2015.2511743.

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 Creators:
Hauberg, S.1, Author
Feragen, A.1, Author
Enficiaud, Raffi2, Author           
Black, M. J.2, Author           
Affiliations:
1External Organizations, ou_persistent22              
2Dept. Perceiving Systems, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_1497642              

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Free keywords: Abt. Black
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Language(s): eng - English
 Dates: 2015-12-232016-11-01
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: Hauberg:PAMI:2015
DOI: 10.1109/TPAMI.2015.2511743
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Title: IEEE Transactions on Pattern Analysis and Machine Intelligence
  Other : IEEE Trans. Pattern Anal. Mach. Intell.
Source Genre: Journal
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Affiliations:
Publ. Info: New York : IEEE Computer Society.
Pages: - Volume / Issue: 38 (11) Sequence Number: - Start / End Page: 2298 - 2311 Identifier: ISSN: 0162-8828
CoNE: https://pure.mpg.de/cone/journals/resource/954925479551