Yann Traonmilin

Orcid: 0000-0003-1826-4760

According to our database1, Yann Traonmilin authored at least 27 papers between 2012 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Bibliography

2024
On Strong Basins of Attractions for Non-convex Sparse Spike Estimation: Upper and Lower Bounds.
J. Math. Imaging Vis., January, 2024

Projected Block Coordinate Descent for sparse spike estimation.
CoRR, 2024

2023
Batch-less stochastic gradient descent for compressive learning of deep regularization for image denoising.
CoRR, 2023

Compressive Learning of Deep Regularization for Denoising.
Proceedings of the Scale Space and Variational Methods in Computer Vision, 2023

2022
Compressive Learning for Patch-Based Image Denoising.
SIAM J. Imaging Sci., September, 2022

Fast off-the-grid sparse recovery with over-parametrized projected gradient descent.
Proceedings of the 30th European Signal Processing Conference, 2022

Piecewise linear prediction model for action tracking in sports.
Proceedings of the 30th European Signal Processing Conference, 2022

2021
Sketched Learning for Image Denoising.
Proceedings of the Scale Space and Variational Methods in Computer Vision, 2021

Sur la performance des méthodes convexes et non-convexes de reconstruction de modèles de faible dimension en science des données.
, 2021

2020
Projected Gradient Descent for Non-Convex Sparse Spike Estimation.
IEEE Signal Process. Lett., 2020

An algorithm for non-convex off-the-grid sparse spike estimation with a minimum separation constraint.
CoRR, 2020

The basins of attraction of the global minimizers of non-convex inverse problems with low-dimensional models in infinite dimension.
CoRR, 2020

Statistical Learning Guarantees for Compressive Clustering and Compressive Mixture Modeling.
CoRR, 2020

2018
The basins of attraction of the global minimizers of the non-convex sparse spikes estimation problem.
CoRR, 2018

Is the 1-norm the best convex sparse regularization?
CoRR, 2018

Optimality of 1-norm regularization among weighted 1-norms for sparse recovery: a case study on how to find optimal regularizations.
CoRR, 2018

2017
Compressed sensing in Hilbert spaces.
CoRR, 2017

Compressive Statistical Learning with Random Feature Moments.
CoRR, 2017

Compressive K-means.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Phase unmixing: Multichannel source separation with magnitude constraints.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

2016
A framework for low-complexity signal recovery and its application to structured sparsity.
Proceedings of the 2016 IEEE Information Theory Workshop, 2016

2015
Robust Multi-image Processing with Optimal Sparse Regularization.
J. Math. Imaging Vis., 2015

Stable recovery of low-dimensional cones in Hilbert spaces: One RIP to rule them all.
CoRR, 2015

2014
Relations entre le modèle d'image et le nombre de mesures pour une super-résolution fidèle. (Relations between image model and number of measures for a high fidelity super-resolution).
PhD thesis, 2014

Simultaneous High Dynamic Range and Superresolution Imaging without Regularization.
SIAM J. Imaging Sci., 2014

2013
Outlier Removal Power of the L1-Norm Super-Resolution.
Proceedings of the Scale Space and Variational Methods in Computer Vision, 2013

2012
On the amount of regularization for super-resolution interpolation.
Proceedings of the 20th European Signal Processing Conference, 2012


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