Clustering Signed Networks with the Geometric Mean of Laplacians

MATLAB implementation of the paper:

P. Mercado, F. Tudisco, and M. Hein, Clustering signed networks with the geometric mean of Laplacians. In NIPS 2016.

Content:

• example.m : contains three easy examples showing how to use the code

• SBM_execute.m : runs spectral clustering on signed networks under the stochastic block model (Fig.2 of our paper)

• wikipedia_example_analysis.m : generates plots from Wikipedia experiment (Fig.4 of our paper).

  • The corresponding eigenvectors are precomputed with wikipedia_example.m and are located in the folder Wikipedia/wikipedia_example

Usage:

Let Wpos and Wneg be the positive and negative adjacency matrices, respectively, and numClusters the desired number of clusters. Clusters through the geometric mean Laplacian are computed via

C = clustering_signed_networks_with_geometric_mean_of_Laplacians(Wpos,Wneg,numClusters);

Quick Overview:

Citation:

@incollection{NIPS2016_6164,
title = {Clustering Signed Networks with the Geometric Mean of Laplacians},
author = {Mercado, Pedro and Tudisco, Francesco and Hein, Matthias},
booktitle = {Advances in Neural Information Processing Systems 29},
editor = {D. D. Lee and M. Sugiyama and U. V. Luxburg and I. Guyon and R. Garnett},
pages = {4421--4429},
year = {2016},
publisher = {Curran Associates, Inc.},
url = {http://papers.nips.cc/paper/6164-clustering-signed-networks-with-the-geometric-mean-of-laplacians.pdf}
}