Optimal Laplacian regularization for sparse spectral community detection

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 stateof-the-art spectral techniques for sparse graphs.

Publication
In 2020 IEEE International Conference on Acoustics, Speech and Signal Processing
Lorenzo Dall'Amico
Lorenzo Dall'Amico
Postdoctoral fellow

I am currently a postdoctoral fellow at the ISI foundation in Turin, Italy.