Spectral Clustering of Signed Graphs via Matrix Power Means
International Conference on Machine Learning (ICML), pp. 4526–4536, 2019
Signed graphs encode positive (attractive) and negative (repulsive) relations between nodes. We extend spectral clustering to signed graphs via the one-parameter family of Signed Power Mean Laplacians, defined as the matrix power mean of normalized standard and signless Laplacians of positive and negative edges. We …
Clustering Signed Networks with the Geometric Mean of Laplacians
Advances in Neural Information Processing Systems (NeurIPS), vol. 29, 2016
Signed networks allow to model positive and negative relationships. We analyze existing extensions of spectral clustering to signed networks. It turns out that existing approaches do not recover the ground truth clustering in several situations where either the positive or the negative network structures contain no …