83 citations · 332 across the 27 of their papers we have counts for
4 papers · 1 filter
Community detection in sparse time-evolving graphs with a dynamical Bethe-Hessian
Lorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay
This article considers the problem of community detection in sparse dynamical graphs in which the community structure evolves over time. A fast spectral algorithm based on an exten…
Revisiting the Bethe-Hessian: Improved Community Detection in Sparse Heterogeneous Graphs
Lorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay
Spectral clustering is one of the most popular, yet still incompletely understood, methods for community detection on graphs. This article studies spectral clustering based on the…
Random sampling of bandlimited signals on graphs
Gilles Puy, Nicolas Tremblay, Rémi Gribonval +1
We study the problem of sampling k-bandlimited signals on graphs. We propose two sampling strategies that consist in selecting a small subset of nodes at random. The first strategy…
Accelerated Spectral Clustering Using Graph Filtering Of Random Signals
Nicolas Tremblay, Gilles Puy, Pierre Borgnat +2
We build upon recent advances in graph signal processing to propose a faster spectral clustering algorithm. Indeed, classical spectral clustering is based on the computation of the…