Smoothing graph signals via random spanning forests

Nicolas Tremblay, Simon Barthelmé
GIPSA, Grenoble

Date(s) : 13/03/2020   iCal
14 h 00 min - 15 h 00 min

Smoothing is one way to estimate an underlying graph signal from noisy measurements. This operation can be explicitly written in terms of a simple graph filtering operation. However, on large graphs,exact filtering becomes prohibitive computationally and approximate methods are necessary. Two classical options are polynomial approximations and conjugate gradient methods. We will discuss a novel approach, based on recent results on random spanning forests,thereby uncovering another elegant link between the spectral information of a graph and random processes defined on it.

Reference: Yusuf Y. Pilavci, Pierre-Olivier Amblard, Simon Barthelmé, Nicolas Tremblay “Smoothing graph signal via random spanning forests”

Nicolas TREMBLAY (GIPSA, Grenoble)
Simon BARTHELMÉ (GIPSA, Grenoble)


Site Nord, CMI, Salle de Séminaire R164 (1er étage)


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