UMR 5672

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The Bethe-Hessian matrix for community detection in static and dynamical sparse graphs

Lorenzo Dall'Amico (GIPSA-lab, Grenoble)
When Nov 10, 2020
from 02:00 PM to 03:00 PM
Where M7 101
Attendees Lorenzo Dall'Amico
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Spectral clustering is one of the most popular, yet still incompletely understood, methods for community detection on graphs. This talk presents a spectral clustering method based on the Bethe-Hessian matrix for sparse graphs with arbitrary degree distribution. We propose an algorithm that is capable of retrieving communities in this setting and to accurately estimate the number of communities. Strong connections are made with other commonly used spectral clustering techniques, from both statistical physics and mathematics perspectives. An extension of the Bethe-Hessian approach is then proposed for community detection in sparse dynamical graphs.