Low rank subspace clustering (LRSC)

@article{Vidal2014LowRS,
  title={Low rank subspace clustering (LRSC)},
  author={Ren{\'e} Vidal and Paolo Favaro},
  journal={Pattern Recognition Letters},
  year={2014},
  volume={43},
  pages={47-61}
}
We consider the problem of fitting a union of subspaces to a collection of data points drawn from one or more subspaces and corrupted by noise and/or gross errors. We pose this problem as a non-convex optimization problem, where the goal is to decompose the corrupted data matrix as the sum of a clean and self-expressive dictionary plus a matrix of noise and/or gross errors. By self-expressive we mean a dictionary whose atoms can be expressed as linear combinations of themselves with low-rank… CONTINUE READING
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Low rank subspace clustering ( LRSC )

P. Favaro
2013

Low rank subspace clustering (LRSC)

R. Vidal, P. Favaro
Pattern Recognition Lett. (2013), • 2013

Pattern Recognition Letters xxx (2013) xxx–xxx Please cite this article in press

R. Vidal, P. Favaro
Pattern Recognition Lett. (2013), • 2013

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