A Geometric Analysis of Subspace Clustering with Outliers

@article{Soltanolkotabi2011AGA,
  title={A Geometric Analysis of Subspace Clustering with Outliers},
  author={Mahdi Soltanolkotabi and Emmanuel J. Cand{\`e}s},
  journal={ArXiv},
  year={2011},
  volume={abs/1112.4258}
}
This paper considers the problem of clustering a collection of unlabeled data points assumed to lie near a union of lower dimensional planes. As is common in computer vision or unsupervised learning applications, we do not know in advance how many subspaces there are nor do we have any information about their dimensions. We develop a novel geometric analysis of an algorithm named sparse subspace clustering (SSC) [11], which signicantly broadens the range of problems where it is provably eective… 
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