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A Convex Approach to Subspace Clustering
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2011 (English)In: Proceedings of the 50th IEEE Conference on Decision and Control, 2011, 1467-1472 p.Conference paper, Published paper (Refereed)
Abstract [en]

The identification of multiple affine subspaces from a set of data is of interest in fields such as system identification, data compression, image processing and signal processing and in the literature referred to as subspace clustering. If the origin of each sample would be known, the problem would be trivially solved by applying principal component analysis to samples originated from the same subspace. Now, not knowing what samples that originates from what subspace, the problem becomes considerably more difficult. We present a novel convex formulation for subspace clustering. The proposed method takes the shape of a least-squares problem with sum-of-norms regularization over optimization parameter differences, a generalization of the ℓ1-regularization. The regularization constant is used to trade off fit and the identified number of affine subspaces.

Place, publisher, year, edition, pages
2011. 1467-1472 p.
Keyword [en]
Convex programming, Least squares approximations, Pattern clustering
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-95597DOI: 10.1109/CDC.2011.6161221ISBN: 978-1-61284-799-3 (print)ISBN: 978-1-61284-800-6 (print)OAI: oai:DiVA.org:liu-95597DiVA: diva2:636445
Conference
50th IEEE Conference on Decision and Control, Orlando, FL, USA, 12-15 December, 2011
Available from: 2013-07-10 Created: 2013-07-10 Last updated: 2013-07-10

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Ohlsson, HenrikLjung, Lennart

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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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  • Other style
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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