30 citations · 86 across the 20 of their papers we have counts for
7 papers · 1 filter
Stable safe screening and structured dictionaries for faster L1 regularization
Cassio Fraga Dantas, Rémi Gribonval
In this paper, we propose a way to combine two acceleration techniques for the -regularized least squares problem: safe screening tests, which allow to eliminate useless…
Concentration of the Frobenius norm of generalized matrix inverses
Ivan Dokmanić, Rémi Gribonval
In many applications it is useful to replace the Moore-Penrose pseudoinverse (MPP) by a different generalized inverse with more favorable properties. We may want, for example, to h…
MULAN: A Blind and Off-Grid Method for Multichannel Echo Retrieval
Helena Peic Tukuljac, Antoine Deleforge, Rémi Gribonval
This paper addresses the general problem of blind echo retrieval, i.e., given M sensors measuring in the discrete-time domain M mixtures of K delayed and attenuated copies of an un…
On bayesian estimation and proximity operators
Rémi Gribonval, Mila Nikolova
There are two major routes to address the ubiquitous family of inverse problems appearing in signal and image processing, such as denoising or deblurring. A first route relies on B…
A characterization of proximity operators
Rémi Gribonval, Mila Nikolova
We characterize proximity operators, that is to say functions that map a vector to a solution of a penalized least squares optimization problem. Proximity operators of convex penal…
Is the 1-norm the best convex sparse regularization?
Yann Traonmilin, Samuel Vaiter, Rémi Gribonval
The 1-norm is a good convex regularization for the recovery of sparse vectors from under-determined linear measurements. No other convex regularization seems to surpass its sparse…