Safe squeezing for antisparse coding

Date : 04/10/2019
Catégorie(s) : ,
Lieu : Salle A3.05, Bâtiment Breguet, CentraleSupélec

Speaker Clément Elvira (PANAMA research group, Iniria, CNRS, IRISA – Rennes)

Abstract Spreading the information over all coefficients of a representation is a desirable
property in many applications such as digital communication or machine learning. This
so-called antisparse representation can be obtained by solving a convex program involving a
$\ell_\infty$-norm penalty combined with a quadratic discrepancy. In this talk, we propose a
new methodology, dubbed safe squeezing, to accelerate the computation of antisparse
representation. We describe a test that allows to detect saturated entries in the solution
of the optimization problem. The contribution of these entries is compacted into a single
vector, resulting in a form of dimensionality reduction. We propose two algorithms to solve
the latter lower dimensional problem. Numerical experiments show both the effectiveness of
the saturation detection tests and that the proposed procedures lead to significant
computational gains as compared to existing methods.

Biography Clément Elvira is a postdoctoral researcher at Inria Rennes – Bretagne
atlantique and part of the BECOSE project. He is working under the supervision of Cédric
Herzet, Rémi Gribonval and Charles Soussen. He was a PhD student from october, 2014 to
november, 2017 at CRIStAL in Lille, France, under the supervision of Pierre Chainais and
Nicolas Dobigeon, and he was part of the SigMA group at CRIStAL. Webpage: