Florent Bouchard

Documents

Publications

	Probabilistic PCA From Heteroscedastic Signals: Geometric Framework and Application to Clustering Antoine Collas , Florent Bouchard , Arnaud Breloy , Guillaume Ginolhac , Chengfang Ren IEEE Transactions on Signal Processing, 2021, 69, pp.6546-6560. ⟨10.1109/TSP.2021.3130997⟩ Journal articles hal-03521278v1
	A Riemannian Framework for Low-Rank Structured Elliptical Models Florent Bouchard , Arnaud Breloy , Guillaume Ginolhac , Alexandre Renaux , Frédéric Pascal IEEE Transactions on Signal Processing, 2021, 69, pp.1185-1199. ⟨10.1109/TSP.2021.3054237⟩ Journal articles hal-03273062v1
	Riemannian geometry for compound Gaussian distributions: Application to recursive change detection Florent Bouchard , Ammar Mian , Jialun Zhou , Salem Said , Guillaume Ginolhac Signal Processing, 2020, 176, pp.107716. ⟨10.1016/j.sigpro.2020.107716⟩ Journal articles hal-02972691v1
	Approximate joint diagonalization with Riemannian optimization on the general linear group Florent Bouchard , Bijan Afsari , Jérôme Malick , Marco Congedo SIAM Journal on Matrix Analysis and Applications, 2020, 41 (1), pp.152-170. ⟨10.1137/18M1232838⟩ Journal articles hal-02328480v1
	Intrinsic Cramér–Rao bounds for scatter and shape matrices estimation in CES distributions Arnaud Breloy , Guillaume Ginolhac , Alexandre Renaux , Florent Bouchard IEEE Signal Processing Letters, 2019, 26 (2), pp.262-266. ⟨10.1109/LSP.2018.2886700⟩ Journal articles hal-01975919v1
	Riemannian Optimization and Approximate Joint Diagonalization for Blind Source Separation Florent Bouchard , Jérôme Malick , Marco Congedo IEEE Transactions on Signal Processing, 2018, 66 (8), pp.2041-2054. ⟨10.1109/TSP.2018.2795539⟩ Journal articles hal-01875788v1

	Robust Low-Rank Correlation Fitting Thu Ha Phi , Alexandre Hippert-Ferrer , Florent Bouchard , Arnaud Breloy 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2024), Apr 2024, Séoul, South Korea. pp.9416-9420, ⟨10.1109/ICASSP48485.2024.10446634⟩ Conference papers hal-04642652v1
	Estimation de barycentres sur variétés de Stiefel : une approche par projection Nils Laurent , Florent Bouchard , Salem Said , Nicolas Le Bihan GRETSI 2023 - XXIXème Colloque Francophone de Traitement du Signal et des Images, GRETSI - Groupe de Recherche en Traitement du Signal et des Images, Aug 2023, Grenoble, France Conference papers hal-04228051v1
	Elliptical Wishart Distribution: Maximum Likelihood Estimator from Information Geometry Imen Ayadi , Florent Bouchard , Frédéric Pascal ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Jun 2023, Rhodes Island, Greece. pp.1-5, ⟨10.1109/ICASSP49357.2023.10096222⟩ Conference papers hal-04213775v1
	t-WDA: A novel Discriminant Analysis applied to EEG classification Imen Ayadi , Florent Bouchard , Frédéric Pascal 2023 31st European Signal Processing Conference (EUSIPCO), Sep 2023, Helsinki, Finland. ⟨10.23919/eusipco58844.2023.10289799⟩ Conference papers hal-04249018v1
	Learning Graphical Factor Models with Riemannian Optimization Alexandre Hippert-Ferrer , Florent Bouchard , Ammar Mian , Titouan Vayer , Arnaud Breloy Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2023), Sep 2023, Torino, Italy. ⟨10.1007/978-3-031-43421-1_21⟩ Conference papers hal-04249001v1
	Distribution matricielle t-Wishart : géométrie d'information, estimation et application pour la classification de signaux EEG Imen Ayadi , Florent Bouchard , Frédéric Pascal GRETSI 2023 - XXIXème Colloque Francophone de Traitement du Signal et des Images, Aug 2023, Grenoble, France Conference papers hal-04226626v1
	Optimisation Riemannienne pour l'apprentissage de graphes structurés Alexandre Hippert-Ferrer , Florent Bouchard , Ammar Mian , Titouan Vayer , Arnaud Breloy GRETSI 2023 - XXIXème Colloque Francophone de Traitement du Signal et des Images, Aug 2023, Grenoble, France. pp.585-588 Conference papers hal-04228029v1
	ON THE USE OF GEODESIC TRIANGLES BETWEEN GAUSSIAN DISTRIBUTIONS FOR CLASSIFICATION PROBLEMS Antoine Collas , Florent Bouchard , Guillaume Ginolhac , Arnaud Breloy , Chengfang Ren 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2022), May 2022, Singapour, Singapore. ⟨10.1109/ICASSP43922.2022.9747872⟩ Conference papers hal-03752879v1
	Riemannian classification of EEG signals with missing values Alexandre Hippert-Ferrer , Ammar Mian , Florent Bouchard , Frédéric Pascal 30th European Signal Processing Conference (EUSIPCO 2022), Aug 2022, Belgrade, Serbia. ⟨10.23919/eusipco55093.2022.9909703⟩ Conference papers hal-03856816v1
	On-line Kronecker Product Structured Covariance Estimation with Riemannian geometry for t-distributed data Florent Bouchard , Arnaud Breloy , Ammar Mian , Guillaume Ginolhac The 29th European Signal Processing Conference (EUSIPCO 2021), Aug 2021, Dublin, Ireland. pp.856-859, ⟨10.23919/EUSIPCO54536.2021.9616101⟩ Conference papers hal-03521267v1
	A Tyler-type estimator of location and scatter leveraging Riemannian optimization Antoine Collas , Florent Bouchard , A. Breloy , Chengfang Ren , Guillaume Ginolhac 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Jun 2021, Toronto, Canada. ⟨10.1109/ICASSP39728.2021.9414974⟩ Conference papers hal-03144104v1
	A Riemannian approach to blind separation of t-distributed sources Florent Bouchard , Arnaud Breloy , Guillaume Ginolhac , Alexandre Renaux 2020 28th European Signal Processing Conference (EUSIPCO), Jan 2021, Amsterdam, Netherlands. ⟨10.23919/eusipco47968.2020.9287783⟩ Conference papers hal-02988356v1
	Riemannian framework for robust covariance matrix estimation in spiked models Florent Bouchard , Arnaud Breloy , Guillaume Ginolhac , Frédéric Pascal ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2020, Barcelona, Spain. ⟨10.1109/icassp40776.2020.9054726⟩ Conference papers hal-02571084v1
	Riemannian geometry and Cramér-Rao bound for blind separation of Gaussian sources Florent Bouchard , Arnaud Breloy , Alexandre Renaux , Guillaume Ginolhac ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2020, Barcelona, Spain. ⟨10.1109/icassp40776.2020.9052996⟩ Conference papers hal-02571093v1
	Random Matrix Improved Covariance Estimation for a Large Class of Metrics Malik Tiomoko , Florent Bouchard , Guillaume Ginolhac , Romain Couillet ICML 2019 - 36th International Conference on Machine Learning, Jun 2019, Long Beach, United States Conference papers hal-02152121v1
	Bornes de Cramér-Rao Intrinsèques pour l'estimation de la matrice de dispersion normalisée dans les distributions elliptiques Florent Bouchard , Arnaud Breloy , Alexandre Renaux , Guillaume Ginolhac GRETSI 2019 - XXVIIème Colloque francophone de traitement du signal et des images, Aug 2019, Lille, France Conference papers hal-02388701v1
	Dimensionality Reduction for BCI classification using Riemannian geometry Pedro Luiz Coelho Rodrigues , Florent Bouchard , Marco Congedo , Christian Jutten BCI 2017 - 7th International Brain-Computer Interface Conference, Gernot R. Müller-Putz, Sep 2017, Graz, Austria. ⟨10.3217/978-3-85125-533-1-16⟩ Conference papers hal-01591258v1
	A Closed-Form Unsupervised Geometry-Aware Dimensionality Reduction Method in the Riemannian Manifold of SPD Matrices Marco Congedo , Pedro Luiz Coelho Rodrigues , Florent Bouchard , Alexandre Barachant , Christian Jutten EMBC 2017 - 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE, Jul 2017, Jeju Island, South Korea. pp.3198-3201, ⟨10.1109/EMBC.2017.8037537⟩ Conference papers hal-01563153v1
	Borne de Cramér-Rao intrinsèque pour la matrice de covariance des distributions elliptiques complexes Arnaud Breloy , Alexandre Renaux , Guillaume Ginolhac , Florent Bouchard GRETSI 2017 - XXVIème Colloque francophone de traitement du signal et des images, Sep 2017, Juan-Les-Pins, France Conference papers hal-01586939v1
	Réduction de dimension pour la Séparation Aveugle de Sources Florent Bouchard , Pedro Luiz Coelho Rodrigues , Jérôme Malick , Marco Congedo GRETSI 2017 - XXVIème Colloque francophone de traitement du signal et des images, Sep 2017, Juan-Les-Pins, France Conference papers hal-01589766v1
	Géométrie Riemannienne appliquée à la réduction de la dimension de signaux EEG pour les interfaces cerveau-machine Pedro Luiz Coelho Rodrigues , Florent Bouchard , Marco Congedo , Christian Jutten GRETSI 2017 - XXVIème Colloque francophone de traitement du signal et des images, Cédric Richard; Marc Antonini, Sep 2017, Juan-Les-Pins, France Conference papers hal-01591252v1
	Approximate Joint Diagonalization According to the Natural Riemannian Distance Florent Bouchard , Jérôme Malick , Marco Congedo LVA/ICA 2017 - 13th International Conference on Latent Variable Analysis and Signal Separation, Feb 2017, Grenoble, France. pp.290-299, ⟨10.1007/978-3-319-53547-0_28⟩ Conference papers hal-01551813v1
	Approximate Joint Diagonalization within the Riemannian Geometry Framework Florent Bouchard , Louis Korczowski , Jérôme Malick , Marco Congedo EUSIPCO 2016 - 24th European Signal Processing Conference, Aug 2016, Budapest, Hungary. pp.210-214, ⟨10.1109/EUSIPCO.2016.7760240⟩ Conference papers hal-01370052v1

	The Fisher-Rao geometry of CES distributions Florent Bouchard , Arnaud Breloy , Antoine Collas , Alexandre Renaux , Guillaume Ginolhac Springer. Elliptical Distributions in Signal Processing, inPress Book sections hal-04225646v1

Florent Bouchard

Publications

Probabilistic PCA From Heteroscedastic Signals: Geometric Framework and Application to Clustering

A Riemannian Framework for Low-Rank Structured Elliptical Models

Riemannian geometry for compound Gaussian distributions: Application to recursive change detection

Approximate joint diagonalization with Riemannian optimization on the general linear group

Intrinsic Cramér–Rao bounds for scatter and shape matrices estimation in CES distributions

Riemannian Optimization and Approximate Joint Diagonalization for Blind Source Separation

Robust Low-Rank Correlation Fitting

Estimation de barycentres sur variétés de Stiefel : une approche par projection

Elliptical Wishart Distribution: Maximum Likelihood Estimator from Information Geometry

t-WDA: A novel Discriminant Analysis applied to EEG classification

Learning Graphical Factor Models with Riemannian Optimization

Distribution matricielle t-Wishart : géométrie d'information, estimation et application pour la classification de signaux EEG

Optimisation Riemannienne pour l'apprentissage de graphes structurés

ON THE USE OF GEODESIC TRIANGLES BETWEEN GAUSSIAN DISTRIBUTIONS FOR CLASSIFICATION PROBLEMS

Riemannian classification of EEG signals with missing values

On-line Kronecker Product Structured Covariance Estimation with Riemannian geometry for t-distributed data

A Tyler-type estimator of location and scatter leveraging Riemannian optimization

A Riemannian approach to blind separation of t-distributed sources

Riemannian framework for robust covariance matrix estimation in spiked models

Riemannian geometry and Cramér-Rao bound for blind separation of Gaussian sources

Random Matrix Improved Covariance Estimation for a Large Class of Metrics

Bornes de Cramér-Rao Intrinsèques pour l'estimation de la matrice de dispersion normalisée dans les distributions elliptiques

Dimensionality Reduction for BCI classification using Riemannian geometry

A Closed-Form Unsupervised Geometry-Aware Dimensionality Reduction Method in the Riemannian Manifold of SPD Matrices

Borne de Cramér-Rao intrinsèque pour la matrice de covariance des distributions elliptiques complexes

Réduction de dimension pour la Séparation Aveugle de Sources

Géométrie Riemannienne appliquée à la réduction de la dimension de signaux EEG pour les interfaces cerveau-machine

Approximate Joint Diagonalization According to the Natural Riemannian Distance

Approximate Joint Diagonalization within the Riemannian Geometry Framework

The Fisher-Rao geometry of CES distributions