FRUMAM

Agenda

séminaire

• Vendredi 22 juin 14:00-15:00 - no-reply@math.cnrs.fr

  Hugo RAGUET - Cut-pursuit algorithm for regularizing nonsmooth functionals with graph total variation

  Résumé : I will present an extension of the cut-pursuit algorithm, introduced by Landrieu and Obozinski (2017), to the _graph total-variation_ regularization of functions with a separable nondifferentiable part.We propose a modified algorithmic scheme as well as adapted proofs of convergence. We also present a heuristic approach for handling the cases in which the values associated to each vertex of the graph are multidimensional.The performance of our algorithm, which we demonstrate on difficult, ill-conditioned large-scale inverse and learning problems, is such that it may in practice extend the scope of application of the total-variation regularization. -This is a joint work with Loïc Landrieu (IGN, LaSTIG MATIS). -Landrieu, L. and Obozinski, G. « Cut pursuit : Fast algorithms to learn piecewiseconstant functions on general weighted graphs ». SIAM Journal on ImagingSciences, 10(4):1724–1766, 2017. https://www.researchgate.net/scientific-contributions/2046330849_Hugo_Raguet http://1a7r0ch3.github.io Hugo RAGUET [

  Lieu : CMI, salle de séminaire R164 (1er étage)

  Notes de dernières minutes : http://www.i2m.univ-amu.fr/Seminaire-Signal-et-Apprentissage?id_evenement=2377

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