Optimal Laplacian Regularization for Sparse Spectral Community Detection

Lorenzo Dall'Amico; Romain Couillet; Nicolas Tremblay

ICASSP 2020accepted0 citations

Optimal Laplacian Regularization for Sparse Spectral Community Detection

Lorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay

Abstract

Regularization of the classical Laplacian matrices was empirically shown to improve spectral clustering in sparse networks. It was observed that small regularizations are preferable, but this point was left as a heuristic argument. In this paper we formally determine a proper regularization which is intimately related to alternative state-of-the-art spectral techniques for sparse graphs.

BibTeX

@inproceedings{icassp2020_optimallaplacian,
  title = {Optimal Laplacian Regularization for Sparse Spectral Community Detection},
  author = {Lorenzo Dall'Amico and Romain Couillet and Nicolas Tremblay},
  booktitle = {ICASSP 2020},
  year = {2020}
}