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Florent Bouchard
Florent Bouchard
L2S, CNRS, CentraleSupélec, Univ. Paris Saclay
Verified email at centralesupelec.fr - Homepage
Title
Cited by
Cited by
Year
Intrinsic cramér–rao bounds for scatter and shape matrices estimation in ces distributions
A Breloy, G Ginolhac, A Renaux, F Bouchard
IEEE Signal Processing Letters 26 (2), 262-266, 2018
232018
Riemannian optimization and approximate joint diagonalization for blind source separation
F Bouchard, J Malick, M Congedo
IEEE Transactions on Signal Processing 66 (8), 2041-2054, 2018
212018
Dimensionality Reduction for BCI classification using Riemannian geometry
PLC Rodrigues, F Bouchard, M Congedo, C Jutten
BCI 2017-7th International Brain-Computer Interface Conference, 2017
182017
Approximate joint diagonalization with Riemannian optimization on the general linear group
F Bouchard, B Afsari, J Malick, M Congedo
SIAM Journal on Matrix Analysis and Applications 41 (1), 152-170, 2020
132020
A closed-form unsupervised geometry-aware dimensionality reduction method in the Riemannian Manifold of SPD matrices
M Congedo, PLC Rodrigues, F Bouchard, A Barachant, C Jutten
2017 39th Annual International Conference of the IEEE Engineering in …, 2017
132017
Random matrix improved covariance estimation for a large class of metrics
M Tiomoko, R Couillet, F Bouchard, G Ginolhac
International Conference on Machine Learning, 6254-6263, 2019
112019
A Riemannian framework for low-rank structured elliptical models
F Bouchard, A Breloy, G Ginolhac, A Renaux, F Pascal
IEEE Transactions on Signal Processing 69, 1185-1199, 2021
82021
Riemannian geometry for compound Gaussian distributions: Application to recursive change detection
F Bouchard, A Mian, J Zhou, S Said, G Ginolhac, Y Berthoumieu
Signal Processing 176, 107716, 2020
62020
Approximate joint diagonalization according to the natural Riemannian distance
F Bouchard, J Malick, M Congedo
Latent Variable Analysis and Signal Separation: 13th International …, 2017
62017
Approximate joint diagonalization within the Riemannian geometry framework
F Bouchard, L Korczowski, J Malick, M Congedo
2016 24th European Signal Processing Conference (EUSIPCO), 210-214, 2016
62016
Mining the bilinear structure of data with approximate joint diagonalization
L Korczowski, F Bouchard, C Jutten, M Congedo
2016 24th European Signal Processing Conference (EUSIPCO), 667-671, 2016
52016
A Tyler-type estimator of location and scatter leveraging Riemannian optimization
A Collas, F Bouchard, A Breloy, C Ren, G Ginolhac, JP Ovarlez
ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021
32021
Riemannian geometry and Cramér-Rao bound for blind separation of Gaussian sources
F Bouchard, A Breloy, A Renaux, G Ginolhac
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
32020
On the Use of Geodesic Triangles between Gaussian Distributions for Classification Problems
A Collas, F Bouchard, G Ginolhac, A Breloy, C Ren, JP Ovarlez
ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022
22022
Probabilistic PCA From Heteroscedastic Signals: Geometric Framework and Application to Clustering
A Collas, F Bouchard, A Breloy, G Ginolhac, C Ren, JP Ovarlez
IEEE Transactions on Signal Processing 69, 6546-6560, 2021
22021
Riemannian framework for robust covariance matrix estimation in spiked models
F Bouchard, A Breloy, G Ginolhac, F Pascal
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
22020
Géométrie Riemannienne appliquée à la réduction de la dimension de signaux EEG pour les interfaces cerveau-machine
PLC Rodrigues, F Bouchard, M Congedo, C Jutten
GRETSI 2017-XXVIème Colloque francophone de traitement du signal et des images, 2017
12017
Réduction de dimension pour la Séparation Aveugle de Sources
F Bouchard, PLC Rodrigues, J Malick, M Congedo
GRETSI 2017-XXVIème Colloque francophone de traitement du signal et des images, 2017
12017
Borne de Cramér-Rao intrinsèque pour la matrice de covariance des distributions elliptiques complexes
A Breloy, A Renaux, G Ginolhac, F Bouchard
GRETSI 2017-XXVIème Colloque francophone de traitement du signal et des images, 2017
12017
Learning Graphical Factor Models with Riemannian Optimization
A Hippert-Ferrer, F Bouchard, A Mian, T Vayer, A Breloy
arXiv preprint arXiv:2210.11950, 2022
2022
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