most citedProjected gradient descent for non-convex sparse spike estimation

21 citations · 22 across the 4 of their papers we have counts for

collaborators

5 papers

cs.IT2020

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…

eess.SP202021 cited

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…

math.ST2019

Maximum entropy methods for texture synthesis: theory and practice

Valentin De Bortoli, Agnes Desolneux, Alain Durmus +2

Recent years have seen the rise of convolutional neural network techniques in exemplar-based image synthesis. These methods often rely on the minimization of some variational formu…

cs.CV2019

Patch redundancy in images: a statistical testing framework and some applications

De Bortoli Valentin, Desolneux Agnès, Galerne Bruno +1

In this work we introduce a statistical framework in order to analyze the spatial redundancy in natural images. This notion of spatial redundancy must be defined locally and thus w…

cs.CV20191 cited

Macrocanonical Models for Texture Synthesis

De Bortoli Valentin, Desolneux Agnès, Galerne Bruno +1

In this article we consider macrocanonical models for texture synthesis. In these models samples are generated given an input texture image and a set of features which should be ma…