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ORCIDYann Traonmilin
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2020 – today
- 2024
[j6]Yann Traonmilin, Jean-François Aujol, Pierre-Jean Bénard, Arthur Leclaire:
On Strong Basins of Attractions for Non-convex Sparse Spike Estimation: Upper and Lower Bounds. J. Math. Imaging Vis. 66(1): 57-74 (2024)- [j5]Hui Shi, Yann Traonmilin, Jean-François Aujol:
Batch-Less Stochastic Gradient Descent for Compressive Learning of Deep Regularization for Image Denoising. J. Math. Imaging Vis. 66(4): 464-477 (2024) - [c11]Pierre-Jean Bénard, Yann Traonmilin, Jean-François Aujol:
Projected Block Coordinate Descent for Sparse Spike Estimation. EUSIPCO 2024: 2667-2671 - [c10]Antoine Guennec, Jean-François Aujol, Yann Traonmilin:
Adaptive Parameter Selection for Gradient-Sparse Plus Low Patch-Rank Recovery: Application to Image Decomposition. EUSIPCO 2024: 2672-2676 - [i13]Pierre-Jean Bénard, Yann Traonmilin, Jean-François Aujol:
Projected Block Coordinate Descent for sparse spike estimation. CoRR abs/2402.12021 (2024) - 2023
- [c9]Hui Shi, Yann Traonmilin, Jean-François Aujol:
Compressive Learning of Deep Regularization for Denoising. SSVM 2023: 162-174 - [i12]Hui Shi, Yann Traonmilin, Jean-François Aujol:
Batch-less stochastic gradient descent for compressive learning of deep regularization for image denoising. CoRR abs/2310.03085 (2023) - 2022
- [j4]Hui Shi
, Yann Traonmilin, Jean-François Aujol:
Compressive Learning for Patch-Based Image Denoising. SIAM J. Imaging Sci. 15(3): 1184-1212 (2022) - [c8]Axel Baldanza, Jean-François Aujol, Yann Traonmilin, François Alary:
Piecewise linear prediction model for action tracking in sports. EUSIPCO 2022: 518-522 - [c7]Pierre-Jean Bénard, Yann Traonmilin, Jean-François Aujol:
Fast off-the-grid sparse recovery with over-parametrized projected gradient descent. EUSIPCO 2022: 2206-2210 - 2021
- [b2]Yann Traonmilin:
Sur la performance des méthodes convexes et non-convexes de reconstruction de modèles de faible dimension en science des données. University of Bordeaux, France, 2021 - [c6]Hui Shi, Yann Traonmilin, Jean-François Aujol:
Sketched Learning for Image Denoising. SSVM 2021: 281-293 - 2020
- [j3]Yann Traonmilin, Jean-François Aujol, Arthur Leclaire:
Projected Gradient Descent for Non-Convex Sparse Spike Estimation. IEEE Signal Process. Lett. 27: 1110-1114 (2020) - [i11]Rémi Gribonval, Gilles Blanchard, Nicolas Keriven, Yann Traonmilin:
Statistical Learning Guarantees for Compressive Clustering and Compressive Mixture Modeling. CoRR abs/2004.08085 (2020) - [i10]Yann Traonmilin, Jean-François Aujol, Arthur Leclaire:
The basins of attraction of the global minimizers of non-convex inverse problems with low-dimensional models in infinite dimension. CoRR abs/2009.08670 (2020) - [i9]Yann Traonmilin, Jean-François Aujol, Arthur Leclaire:
An algorithm for non-convex off-the-grid sparse spike estimation with a minimum separation constraint. CoRR abs/2012.01262 (2020)
2010 – 2019
- 2018
- [i8]Yann Traonmilin, Samuel Vaiter:
Optimality of 1-norm regularization among weighted 1-norms for sparse recovery: a case study on how to find optimal regularizations. CoRR abs/1803.00773 (2018) - [i7]Yann Traonmilin, Samuel Vaiter, Rémi Gribonval:
Is the 1-norm the best convex sparse regularization? CoRR abs/1806.08690 (2018) - [i6]Yann Traonmilin, Jean-François Aujol:
The basins of attraction of the global minimizers of the non-convex sparse spikes estimation problem. CoRR abs/1811.12000 (2018) - 2017
- [c5]Antoine Deleforge, Yann Traonmilin:
Phase unmixing: Multichannel source separation with magnitude constraints. ICASSP 2017: 161-165 - [c4]Nicolas Keriven, Nicolas Tremblay, Yann Traonmilin, Rémi Gribonval:
Compressive K-means. ICASSP 2017: 6369-6373 - [i5]Yann Traonmilin, Gilles Puy, Rémi Gribonval, Mike E. Davies:
Compressed sensing in Hilbert spaces. CoRR abs/1702.04917 (2017) - [i4]Rémi Gribonval, Gilles Blanchard, Nicolas Keriven, Yann Traonmilin:
Compressive Statistical Learning with Random Feature Moments. CoRR abs/1706.07180 (2017) - 2016
- [c3]Yann Traonmilin, Rémi Gribonval:
A framework for low-complexity signal recovery and its application to structured sparsity. ITW 2016: 156-160 - [i3]Antoine Deleforge, Yann Traonmilin:
Phase Unmixing : Multichannel Source Separation with Magnitude Constraints. CoRR abs/1609.09744 (2016) - [i2]Nicolas Keriven, Nicolas Tremblay, Yann Traonmilin, Rémi Gribonval:
Compressive K-means. CoRR abs/1610.08738 (2016) - 2015
- [j2]Yann Traonmilin, Saïd Ladjal, Andrés Almansa:
Robust Multi-image Processing with Optimal Sparse Regularization. J. Math. Imaging Vis. 51(3): 413-429 (2015) - [i1]Yann Traonmilin, Rémi Gribonval:
Stable recovery of low-dimensional cones in Hilbert spaces: One RIP to rule them all. CoRR abs/1510.00504 (2015) - 2014
- [b1]Yann Traonmilin:
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). Télécom ParisTech, France, 2014 - [j1]Yann Traonmilin, Cecilia Aguerrebere:
Simultaneous High Dynamic Range and Superresolution Imaging without Regularization. SIAM J. Imaging Sci. 7(3): 1624-1644 (2014) - 2013
- [c2]Yann Traonmilin, Saïd Ladjal, Andrés Almansa:
Outlier Removal Power of the L1-Norm Super-Resolution. SSVM 2013: 198-209 - 2012
- [c1]Yann Traonmilin, Saïd Ladjal, Andrés Almansa:
On the amount of regularization for super-resolution interpolation. EUSIPCO 2012: 380-384
Coauthor Index
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last updated on 2024-11-07 20:31 CET by the dblp team
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