RW kernels, spanning forests and multiscale analysis on graphs.

par Luca Avena

jeudi 2 mars 2017, 14:00 → 15:00 Europe/Paris

Fokko du Cloux (La Doua, ICJ, Bât. Braconnier)

We use ideas from large-scale stochastic dynamics to build a multiresolution scheme to analyse arbitrary functions on graphs. These types of problems emerge naturally in the context of signal processing. The goal is to obtain successive approximations at different scales of arbitrary functions on graphs which are used for signal classification, reconstruction and data compression.When the signal is defined on a graph having enough regularity structures, several methods (such as wavelets) are available in the literature and used in practice. When the regularity structure of the graph is lacking, very few methods are known.Our work aims at addressing this issue by using random spanning forests, loop-erased walks, determinantal structures, random walk kernels and intertwining of Markov chains. Joint work with Castel, Gaudilliere and Melot.