Corpus ID: 4475548

Signed Laplacian for spectral clustering revisited

  title={Signed Laplacian for spectral clustering revisited},
  author={Andrew V. Knyazev},
  • A. Knyazev
  • Published 5 January 2017
  • Mathematics, Computer Science
  • ArXiv
Classical spectral clustering is based on a spectral decomposition of a graph Laplacian, obtained from a graph adjacency matrix representing positive graph edge weights describing similarities of graph vertices. In signed graphs, the graph edge weights can be negative to describe disparities of graph vertices, for example, negative correlations in the data. Negative weights lead to possible negative spectrum of the standard graph Laplacian, which is cured by defining a signed Laplacian. We… Expand
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