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eess.SP2024
Towards optimal algorithms for the recovery of low-dimensional models with linear rates
Yann Traonmilin, Jean François Aujol, Antoine Guennec
We consider the problem of recovering elements of a low-dimensional model from linear measurements. From signal and image processing to inverse problems in data science, this quest…
eess.SP2022
Fast off-the-grid sparse recovery with over-parametrized projected gradient descent
Pierre-Jean Bénard, Yann Traonmilin, Jean-François Aujol
We consider the problem of recovering off-the-grid spikes from Fourier measurements. Successful methods such as sliding Frank-Wolfe and continuous orthogonal matching pursuit (OMP)…
eess.SP2021
A theory of optimal convex regularization for low-dimensional recovery
Yann Traonmilin, Rémi Gribonval, Samuel Vaiter
We consider the problem of recovering elements of a low-dimensional model from under-determined linear measurements. To perform recovery, we consider the minimization of a convex r…