Large margin filtering for Signal Sequence Labeling. - Rémi Flamary; Benjamin Labbé; Alain Rakotomamonjy (ICASSP, 2010)

Filtrage vaste marge pour l'étiquetage séquentiel à noyaux de signaux - Rémi Flamary; Benjamin Labbé; Alain Rakotomamonjy (CoRR, 2010)

Spoken WordCloud: Clustering recurrent patterns in speech. - Rémi Flamary; Xavier Anguera; Nuria Oliver (CBMI, 2011)

Selecting from an infinite set of features in SVM. - Rémi Flamary; Florian Yger; Alain Rakotomamonjy (ESANN, 2011)

Decoding finger movements from ECoG signals using switching linear models - Rémi Flamary; Alain Rakotomamonjy (CoRR, 2011)

Handling uncertainties in SVM classification - Emilie Niaf; Rémi Flamary; Carole Lartizien; Stéphane Canu (CoRR, 2011)

ellp-ellq Penalty for Sparse Linear and Sparse Multiple Kernel Multitask Learning. - Alain Rakotomamonjy; Rémi Flamary; Gilles Gasso; Stéphane Canu (IEEE Trans. Neural Networks, 2011)

Apprentissage statistique pour le signal: applications aux interfaces cerveau-machine. (Machine learning for signal processing : applications to Brain Computer Interfaces). - Rémi Flamary (2011)

Discovering relevant spatial filterbanks for VHR image classification. - Devis Tuia; Mauro Dalla Mura; Michele Volpi; Rémi Flamary; Alain Rakotomamonjy (ICPR, 2012)

Large Margin Filtering. - Rémi Flamary; Devis Tuia; Benjamin Labbé; Gustavo Camps-Valls; Alain Rakotomamonjy (IEEE Trans. Signal Process., 2012)

Kernel LMS algorithm with forward-backward splitting for dictionary learning. - Wei Gao 021; Jie Chen 022; Cédric Richard; Jianguo Huang; Rémi Flamary (ICASSP, 2013)

Create the relevant spatial filterbank in the hyperspectral jungle. - Devis Tuia; Michele Volpi; Mauro Dalla Mura; Alain Rakotomamonjy; Rémi Flamary (IGARSS, 2013)

Learning with infinitely many features. - Alain Rakotomamonjy; Rémi Flamary; Florian Yger (Mach. Learn., 2013)

Active set strategy for high-dimensional non-convex sparse optimization problems. - Aurelie Boisbunon; Rémi Flamary; Alain Rakotomamonjy (ICASSP, 2014)

Computer-aided diagnostic system for prostate cancer detection and characterization combining learned dictionaries and supervised classification. - Jérôme Lehaire; Rémi Flamary; Olivier Rouvière; Carole Lartizien (ICIP, 2014)

SVM with feature selection and smooth prediction in images: Application to CAD of prostate cancer. - Emilie Niaf; Rémi Flamary; Alain Rakotomamonjy; Olivier Rouvière; Carole Lartizien (ICIP, 2014)

Distributed image reconstruction for very large arrays in radio astronomy. - André Ferrari; David Mary; Rémi Flamary; Cédric Richard (SAM, 2014)

Domain Adaptation with Regularized Optimal Transport. - Nicolas Courty; Rémi Flamary; Devis Tuia (ECML/PKDD (1), 2014)

Mixed-Norm Regularization for Brain Decoding. - Rémi Flamary; Nisrine Jrad; Ronald Phlypo; Marco Congedo; Alain Rakotomamonjy (Comput. Math. Methods Medicine, 2014)

Automatic Feature Learning for Spatio-Spectral Image Classification With Sparse SVM. - Devis Tuia; Michele Volpi; Mauro Dalla Mura; Alain Rakotomamonjy; Rémi Flamary (IEEE Trans. Geosci. Remote. Sens., 2014)

Kernel-Based Learning From Both Qualitative and Quantitative Labels: Application to Prostate Cancer Diagnosis Based on Multiparametric MR Imaging. - Emilie Niaf; Rémi Flamary; Olivier Rouvière; Carole Lartizien; Stéphane Canu (IEEE Trans. Image Process., 2014)

Nonconvex Regularizations for Feature Selection in Ranking With Sparse SVM. - Léa Laporte; Rémi Flamary; Stéphane Canu; Sébastien Déjean; Josiane Mothe (IEEE Trans. Neural Networks Learn. Syst., 2014)

Importance sampling strategy for non-convex randomized block-coordinate descent. - Rémi Flamary; Alain Rakotomamonjy; Gilles Gasso (CAMSAP, 2015)

To be or not to be convex? A study on regularization in hyperspectral image classification. - Devis Tuia; Rémi Flamary; Michel Barlaud (IGARSS, 2015)

Multitemporal classification without new labels: A solution with optimal transport. - Devis Tuia; Rémi Flamary; Alain Rakotomamonjy; Nicolas Courty (MultiTemp, 2015)

Non-convex Regularizations for Feature Selection in Ranking With Sparse SVM. - Léa Laporte; Rémi Flamary; Stéphane Canu; Sébastien Déjean; Josiane Mothe (CoRR, 2015)

Generalized conditional gradient: analysis of convergence and applications. - Alain Rakotomamonjy; Rémi Flamary; Nicolas Courty (CoRR, 2015)

DC Proximal Newton for Non-Convex Optimization Problems. - Alain Rakotomamonjy; Rémi Flamary; Gilles Gasso (CoRR, 2015)

Analysis of Multitemporal Classification Techniques for Forecasting Image Time Series. - Rémi Flamary; Mathieu Fauvel; Mauro Dalla Mura; Silvia Valero (IEEE Geosci. Remote. Sens. Lett., 2015)

Doubly compressed diffusion LMS over adaptive networks. - Ibrahim El Khalil Harrane; Rémi Flamary; Cédric Richard (ACSSC, 2016)

Toward privacy-preserving diffusion strategies for adaptation and learning over networks. - Ibrahim El Khalil Harrane; Rémi Flamary; Cédric Richard (EUSIPCO, 2016)

Optimal transport for data fusion in remote sensing. - Nicolas Courty; Rémi Flamary; Devis Tuia; Thomas Corpetti (IGARSS, 2016)

Optimal spectral transportation with application to music transcription. - Rémi Flamary; Cédric Févotte; Nicolas Courty; Valentin Emiya (NIPS, 2016)

Mapping Estimation for Discrete Optimal Transport. - Michaël Perrot; Nicolas Courty; Rémi Flamary; Amaury Habrard (NIPS, 2016)

Supervised planetary unmixing with optimal transport. - Sina Nakhostin; Nicolas Courty; Rémi Flamary; Thomas Corpetti (WHISPERS, 2016)

Non-convex regularization in remote sensing. - Devis Tuia; Rémi Flamary; Michel Barlaud (CoRR, 2016)

Multiclass feature learning for hyperspectral image classification: sparse and hierarchical solutions. - Devis Tuia; Rémi Flamary; Nicolas Courty (CoRR, 2016)

Nonconvex Regularization in Remote Sensing. - Devis Tuia; Rémi Flamary; Michel Barlaud (IEEE Trans. Geosci. Remote. Sens., 2016)

DC Proximal Newton for Nonconvex Optimization Problems. - Alain Rakotomamonjy; Rémi Flamary; Gilles Gasso (IEEE Trans. Neural Networks Learn. Syst., 2016)

Multi-frequency image reconstruction for radio-interferometry with self-tuned regularization parameters. - Rita Ammanouil; André Ferrari; Rémi Flamary; Chiara Ferrari; David Mary (EUSIPCO, 2017)

Astronomical image reconstruction with convolutional neural networks. - Rémi Flamary (EUSIPCO, 2017)

Distributed approach for deblurring large images with shift-variant blur. - Rahul Mourya; André Ferrari; Rémi Flamary; Pascal Bianchi; Cédric Richard (EUSIPCO, 2017)

Joint distribution optimal transportation for domain adaptation. - Nicolas Courty; Rémi Flamary; Amaury Habrard; Alain Rakotomamonjy (NIPS, 2017)

Optimal Transport for Domain Adaptation. - Nicolas Courty; Rémi Flamary; Devis Tuia; Alain Rakotomamonjy (IEEE Trans. Pattern Anal. Mach. Intell., 2017)

DeepJDOT: Deep Joint Distribution Optimal Transport for Unsupervised Domain Adaptation. - Bharath Bhushan Damodaran; Benjamin Kellenberger; Rémi Flamary; Devis Tuia; Nicolas Courty (ECCV (4), 2018)

Learning Wasserstein Embeddings. - Nicolas Courty; Rémi Flamary; Mélanie Ducoffe (ICLR (Poster), 2018)

Large Scale Optimal Transport and Mapping Estimation. - Vivien Seguy; Bharath Bhushan Damodaran; Rémi Flamary; Nicolas Courty; Antoine Rolet; Mathieu Blondel (ICLR (Poster), 2018)

Wasserstein Distance Measure Machines. - Alain Rakotomamonjy; Abraham Traoré; Maxime Berar; Rémi Flamary; Nicolas Courty (CoRR, 2018)

Optimal Transport for structured data. - Titouan Vayer; Laetitia Chapel; Rémi Flamary; Romain Tavenard; Nicolas Courty (CoRR, 2018)

Fused Gromov-Wasserstein distance for structured objects: theoretical foundations and mathematical properties. - Titouan Vayer; Laetitia Chapel; Rémi Flamary; Romain Tavenard; Nicolas Courty (CoRR, 2018)

Wasserstein discriminant analysis. - Rémi Flamary; Marco Cuturi; Nicolas Courty; Alain Rakotomamonjy (Mach. Learn., 2018)

Optimal Transport for Multi-source Domain Adaptation under Target Shift. - Ievgen Redko; Nicolas Courty; Rémi Flamary; Devis Tuia (AISTATS, 2019)

Optimal Transport for structured data with application on graphs. - Titouan Vayer; Nicolas Courty; Romain Tavenard; Laetitia Chapel; Rémi Flamary (ICML, 2019)

Sliced Gromov-Wasserstein. - Titouan Vayer; Rémi Flamary; Nicolas Courty; Romain Tavenard; Laetitia Chapel (NeurIPS, 2019)

Pushing the right boundaries matters! Wasserstein Adversarial Training for Label Noise. - Bharath Bhushan Damodaran; Kilian Fatras; Sylvain Lobry; Rémi Flamary; Devis Tuia; Nicolas Courty (CoRR, 2019)

Concentration bounds for linear Monge mapping estimation and optimal transport domain adaptation. - Rémi Flamary; Karim Lounici; André Ferrari (CoRR, 2019)

Large scale Lasso with windowed active set for convolutional spike sorting. - Laurent Dragoni; Rémi Flamary; Karim Lounici; Patricia Reynaud-Bouret (CoRR, 2019)

On Reducing the Communication Cost of the Diffusion LMS Algorithm. - Ibrahim El Khalil Harrane; Rémi Flamary; Cédric Richard (IEEE Trans. Signal Inf. Process. over Networks, 2019)

Contextual Semantic Interpretability. - Diego Marcos; Ruth Fong; Sylvain Lobry; Rémi Flamary; Nicolas Courty; Devis Tuia (ACCV (4), 2020)

Learning with minibatch Wasserstein : asymptotic and gradient properties. - Kilian Fatras; Younes Zine; Rémi Flamary; Rémi Gribonval; Nicolas Courty (AISTATS, 2020)

CO-Optimal Transport. - Titouan Vayer; Ievgen Redko; Rémi Flamary; Nicolas Courty (NeurIPS, 2020)

Fused Gromov-Wasserstein Distance for Structured Objects. - Titouan Vayer; Laetitia Chapel; Rémi Flamary; Romain Tavenard; Nicolas Courty (Algorithms, 2020)

Match and Reweight Strategy for Generalized Target Shift. - Alain Rakotomamonjy; Rémi Flamary; Gilles Gasso; Mokhtar Z. Alaya; Maxime Berar; Nicolas Courty (CoRR, 2020)

Provably Convergent Working Set Algorithm for Non-Convex Regularized Regression. - Alain Rakotomamonjy; Rémi Flamary; Gilles Gasso; Joseph Salmon (CoRR, 2020)

Representation Transfer by Optimal Transport. - Xuhong Li 002; Yves Grandvalet; Rémi Flamary; Nicolas Courty; Dejing Dou (CoRR, 2020)

An Entropic Optimal Transport loss for learning deep neural networks under label noise in remote sensing images. - Bharath Bhushan Damodaran; Rémi Flamary; Vivien Seguy; Nicolas Courty (Comput. Vis. Image Underst., 2020)

Unbalanced minibatch Optimal Transport; applications to Domain Adaptation. - Kilian Fatras; Thibault Séjourné; Rémi Flamary; Nicolas Courty (ICML, 2021)

Online Graph Dictionary Learning. - Cédric Vincent-Cuaz; Titouan Vayer; Rémi Flamary; Marco Corneli; Nicolas Courty (ICML, 2021)

Unbalanced Optimal Transport through Non-negative Penalized Linear Regression. - Laetitia Chapel; Rémi Flamary; Haoran Wu; Cédric Févotte; Gilles Gasso (NeurIPS, 2021)

Minibatch optimal transport distances; analysis and applications. - Kilian Fatras; Younes Zine; Szymon Majewski; Rémi Flamary; Rémi Gribonval; Nicolas Courty (CoRR, 2021)

Factored couplings in multi-marginal optimal transport via difference of convex programming. - Quang Huy Tran; Hicham Janati; Ievgen Redko; Rémi Flamary; Nicolas Courty (CoRR, 2021)

Semi-relaxed Gromov Wasserstein divergence with applications on graphs. - Cédric Vincent-Cuaz; Rémi Flamary; Marco Corneli; Titouan Vayer; Nicolas Courty (CoRR, 2021)

POT: Python Optimal Transport. - Rémi Flamary; Nicolas Courty; Alexandre Gramfort; Mokhtar Z. Alaya; Aurélie Boisbunon; Stanislas Chambon; Laetitia Chapel; Adrien Corenflos; Kilian Fatras; Nemo Fournier; Léo Gautheron; Nathalie T. H. Gayraud; et al. (J. Mach. Learn. Res., 2021)

Convergent Working Set Algorithm for Lasso with Non-Convex Sparse Regularizers. - Alain Rakotomamonjy; Rémi Flamary; Joseph Salmon; Gilles Gasso (AISTATS, 2022)

Semi-relaxed Gromov-Wasserstein divergence and applications on graphs. - Cédric Vincent-Cuaz; Rémi Flamary; Marco Corneli; Titouan Vayer; Nicolas Courty (ICLR, 2022)

Learning to Predict Graphs with Fused Gromov-Wasserstein Barycenters. - Luc Brogat-Motte; Rémi Flamary; Céline Brouard; Juho Rousu; Florence d'Alché-Buc (ICML, 2022)

Aligning individual brains with fused unbalanced Gromov Wasserstein. - Alexis Thual; Quang Huy Tran; Tatiana Zemskova; Nicolas Courty; Rémi Flamary; Stanislas Dehaene; Bertrand Thirion (NeurIPS, 2022)

Template based Graph Neural Network with Optimal Transport Distances. - Cédric Vincent-Cuaz; Rémi Flamary; Marco Corneli; Titouan Vayer; Nicolas Courty (NeurIPS, 2022)

Multi-source domain adaptation via weighted joint distributions optimal transport. - Rosanna Turrisi; Rémi Flamary; Alain Rakotomamonjy; Massimiliano Pontil (UAI, 2022)

Wind power predictions from nowcasts to 4-hour forecasts: a learning approach with variable selection. - Dimitri Bouche; Rémi Flamary; Florence d'Alché-Buc; Riwal Plougonven; Marianne Clausel; Jordi Badosa; Philippe Drobinski (CoRR, 2022)

Optimal transport for conditional domain matching and label shift. - Alain Rakotomamonjy; Rémi Flamary; Gilles Gasso; M. El Alaya; Maxime Berar; Nicolas Courty (Mach. Learn., 2022)

Wasserstein Adversarial Regularization for Learning With Label Noise. - Kilian Fatras; Bharath Bhushan Damodaran; Sylvain Lobry; Rémi Flamary; Devis Tuia; Nicolas Courty (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Generating Natural Adversarial Remote Sensing Images. - Jean-Christophe Burnel; Kilian Fatras; Rémi Flamary; Nicolas Courty (IEEE Trans. Geosci. Remote. Sens., 2022)

Time Series Alignment with Global Invariances. - Titouan Vayer; Romain Tavenard; Laetitia Chapel; Rémi Flamary; Nicolas Courty; Yann Soullard (Trans. Mach. Learn. Res., 2022)

Unbalanced CO-optimal Transport. - Quang Huy Tran; Hicham Janati; Nicolas Courty; Rémi Flamary; Ievgen Redko; Pinar Demetci; Ritambhara Singh (AAAI, 2023)

Entropic Wasserstein Component Analysis. - Antoine Collas; Titouan Vayer; Rémi Flamary; Arnaud Breloy (MLSP, 2023)

SNEkhorn: Dimension Reduction with Symmetric Entropic Affinities. - Hugues Van Assel; Titouan Vayer; Rémi Flamary; Nicolas Courty (NeurIPS, 2023)

Convolution Monge Mapping Normalization for learning on sleep data. - Théo Gnassounou; Rémi Flamary; Alexandre Gramfort (NeurIPS, 2023)

Convolutional Monge Mapping Normalization for learning on biosignals. - Théo Gnassounou; Rémi Flamary; Alexandre Gramfort (CoRR, 2023)

Properties of Discrete Sliced Wasserstein Losses. - Eloi Tanguy; Rémi Flamary; Julie Delon (CoRR, 2023)

Optimal Transport with Adaptive Regularisation. - Hugues Van Assel; Titouan Vayer; Rémi Flamary; Nicolas Courty (CoRR, 2023)

Interpolating between Clustering and Dimensionality Reduction with Gromov-Wasserstein. - Hugues Van Assel; Cédric Vincent-Cuaz; Titouan Vayer; Rémi Flamary; Nicolas Courty (CoRR, 2023)

Any2Graph: Deep End-To-End Supervised Graph Prediction With An Optimal Transport Loss. - Paul Krzakala; Junjie Yang; Rémi Flamary; Florence d'Alché-Buc; Charlotte Laclau; Matthieu Labeau (NeurIPS, 2024)

Distributional Reduction: Unifying Dimensionality Reduction and Clustering with Gromov-Wasserstein Projection. - Hugues Van Assel; Cédric Vincent-Cuaz; Nicolas Courty; Rémi Flamary; Pascal Frossard; Titouan Vayer (CoRR, 2024)

Weakly supervised covariance matrices alignment through Stiefel matrices estimation for MEG applications. - Antoine Collas; Rémi Flamary; Alexandre Gramfort (CoRR, 2024)

End-to-end Supervised Prediction of Arbitrary-size Graphs with Partially-Masked Fused Gromov-Wasserstein Matching. - Paul Krzakala; Junjie Yang; Rémi Flamary; Florence d'Alché-Buc; Charlotte Laclau; Matthieu Labeau (CoRR, 2024)

SKADA-Bench: Benchmarking Unsupervised Domain Adaptation Methods with Realistic Validation. - Yanis Lalou; Théo Gnassounou; Antoine Collas; Antoine de Mathelin; Oleksii Kachaiev; Ambroise Odonnat; Alexandre Gramfort; Thomas Moreau 001; Rémi Flamary (CoRR, 2024)

Multi-Source and Test-Time Domain Adaptation on Multivariate Signals using Spatio-Temporal Monge Alignment. - Théo Gnassounou; Antoine Collas; Rémi Flamary; Karim Lounici; Alexandre Gramfort (CoRR, 2024)

Distributional Reduction: Unifying Dimensionality Reduction and Clustering with Gromov-Wasserstein. - Hugues Van Assel; Cédric Vincent-Cuaz; Nicolas Courty; Rémi Flamary; Pascal Frossard; Titouan Vayer (Trans. Mach. Learn. Res., 2025)

SKADA-Bench: Benchmarking Unsupervised Domain Adaptation Methods with Realistic Validation On Diverse Modalities. - Yanis Lalou; Théo Gnassounou; Antoine Collas; Antoine de Mathelin; Ambroise Odonnat; Thomas Moreau 001; Alexandre Gramfort; Rémi Flamary (Trans. Mach. Learn. Res., 2025)

PSDNorm: Test-Time Temporal Normalization for Deep Learning on EEG Signals. - Théo Gnassounou; Antoine Collas; Rémi Flamary; Alexandre Gramfort (CoRR, 2025)

The quest for the GRAph Level autoEncoder (GRALE). - Paul Krzakala; Gabriel Melo; Charlotte Laclau; Florence d'Alché-Buc; Rémi Flamary (CoRR, 2025)

Unsupervised Learning for Optimal Transport plan prediction between unbalanced graphs. - Sonia Mazelet; Rémi Flamary; Bertrand Thirion (CoRR, 2025)