50 citations · 139 across the 24 of their papers we have counts for
4 papers · 1 filter
A biconvex analysis for Lasso l1 reweighting
Sophie M. Fosson
l1 reweighting algorithms are very popular in sparse signal recovery and compressed sensing, since in the practice they have been observed to outperform classical l1 methods. Never…
Non-convex Lasso-kind approach to compressed sensing for finite-valued signals
Sophie M. Fosson
In this paper, we bring together two trends that have recently emerged in sparse signal recovery: the problem of sparse signals that stem from finite alphabets and the techniques t…
Non-convex approach to binary compressed sensing
Sophie M. Fosson
We propose a new approach to the recovery of binary signals in compressed sensing, based on the local minimization of a non-convex cost functional. The desired signal is proved to…
Online optimization in dynamic environments: a regret analysis for sparse problems
Sophie M. Fosson
Time-varying systems are a challenge in many scientific and engineering areas. Usually, estimation of time-varying parameters or signals must be performed online, which calls for t…