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Algebraic-Geometric Methods

  • René Vidal
  • Yi Ma
  • S. Shankar Sastry
Chapter
  • 7.4k Downloads
Part of the Interdisciplinary Applied Mathematics book series (IAM, volume 40)

Abstract

In this chapter, we consider a generalization of PCA in which the given sample points are drawn from an unknown arrangement of subspaces of unknown and possibly different dimensions.

Keywords

Subspace Arrangements Minimum Effective Dimension (MED) Subspace Clustering Model-selection Criteria Multivariate Trimming (MVT) 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag New York 2016

Authors and Affiliations

  • René Vidal
    • 1
  • Yi Ma
    • 2
  • S. Shankar Sastry
    • 3
  1. 1.Center for Imaging Science Department of Biomedical EngineeringJohns Hopkins UniversityBaltimoreUSA
  2. 2.School of Information Science and Technology ShanghaiTech UniversityShanghaiChina
  3. 3.Department of Electrical Engineering and Computer ScienceUniversity of California BerkeleyBerkeleyUSA

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