277 citations · 292 across the 3 of their papers we have counts for
3 papers
stat.ML2017★ 2 cited
Fast Approximate Spectral Clustering for Dynamic Networks
Lionel Martin, Andreas Loukas, Pierre Vandergheynst
Spectral clustering is a widely studied problem, yet its complexity is prohibitive for dynamic graphs of even modest size. We claim that it is possible to reuse information of past…
cs.DS2016★ 13 cited
Fast Eigenspace Approximation using Random Signals
Johan Paratte, Lionel Martin
We focus in this work on the estimation of the first eigenvectors of any graph Laplacian using filtering of Gaussian random signals. We prove that we only need such signals…
cs.IT2014★ 277 cited
GSPBOX: A toolbox for signal processing on graphs
Nathanaël Perraudin, Johan Paratte, David Shuman +4
This document introduces the Graph Signal Processing Toolbox (GSPBox) a framework that can be used to tackle graph related problems with a signal processing approach. It explains t…