22 citations · 82 across the 6 of their papers we have counts for
6 papers
Generalized Matrix Means for Semi-Supervised Learning with Multilayer Graphs
Pedro Mercado, Francesco Tudisco, Matthias Hein
We study the task of semi-supervised learning on multilayer graphs by taking into account both labeled and unlabeled observations together with the information encoded by each indi…
Spectral Clustering of Signed Graphs via Matrix Power Means
Pedro Mercado, Francesco Tudisco, Matthias Hein
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 P…
Node Classification for Signed Social Networks Using Diffuse Interface Methods
Pedro Mercado, Jessica Bosch, Martin Stoll
Signed networks contain both positive and negative kinds of interactions like friendship and enmity. The task of node classification in non-signed graphs has proven to be beneficia…
The Power Mean Laplacian for Multilayer Graph Clustering
Pedro Mercado, Antoine Gautier, Francesco Tudisco +1
Multilayer graphs encode different kind of interactions between the same set of entities. When one wants to cluster such a multilayer graph, the natural question arises how one sho…
Community detection in networks via nonlinear modularity eigenvectors
Francesco Tudisco, Pedro Mercado, Matthias Hein
Revealing a community structure in a network or dataset is a central problem arising in many scientific areas. The modularity function is an established measure quantifying the…
Clustering Signed Networks with the Geometric Mean of Laplacians
Pedro Mercado, Francesco Tudisco, Matthias Hein
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…