21 citations · 21 across the 2 of their papers we have counts for
5 papers
An algorithm for non-convex off-the-grid sparse spike estimation with a minimum separation constraint
Yann Traonmilin, Jean-François Aujol, Arhur Leclaire
Theoretical results show that sparse off-the-grid spikes can be estimated from (possibly compressive) Fourier measurements under a minimum separation assumption. We propose a pract…
Projected gradient descent for non-convex sparse spike estimation
Yann Traonmilin, Jean-François Aujol, Arthur Leclaire
We propose a new algorithm for sparse spike estimation from Fourier measurements. Based on theoretical results on non-convex optimization techniques for off-the-grid sparse spike e…
The basins of attraction of the global minimizers of the non-convex sparse spike estimation problem
Yann Traonmilin, Jean-François Aujol
The sparse spike estimation problem consists in estimating a number of off-the-grid impulsive sources from under-determined linear measurements. Information theoretic results ensur…
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…
Optimality of 1-norm regularization among weighted 1-norms for sparse recovery: a case study on how to find optimal regularizations
Yann Traonmilin, Samuel Vaiter
The 1-norm was proven to be a good convex regularizer for the recovery of sparse vectors from under-determined linear measurements. It has been shown that with an appropriate measu…