Performance Analysis of Spectral Clustering on Compressed, Incomplete and Inaccurate Measurements

@article{Hunter2010PerformanceAO,
  title={Performance Analysis of Spectral Clustering on Compressed, Incomplete and Inaccurate Measurements},
  author={Blake Hunter and Thomas Strohmer},
  journal={CoRR},
  year={2010},
  volume={abs/1011.0997}
}
Spectral clustering is one of the most widely used techniques for extracting the underlying global structure of a data set. Compressed sensing and matrix completion have emerged as prevailing methods for efficiently recovering sparse and partially observed signals respectively. We combine the distance preserving measurements of compressed sensing and matrix completion with the power of robust spectral clustering. Our analysis provides rigorous bounds on how small errors in the affinity matrix… CONTINUE READING
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