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2020 – today
- 2024
[i58]Hugues Van Assel, Cédric Vincent-Cuaz, Nicolas Courty, Rémi Flamary, Pascal Frossard, Titouan Vayer:
Distributional Reduction: Unifying Dimensionality Reduction and Clustering with Gromov-Wasserstein Projection. CoRR abs/2402.02239 (2024)- [i57]Antoine Collas, Rémi Flamary, Alexandre Gramfort:
Weakly supervised covariance matrices alignment through Stiefel matrices estimation for MEG applications. CoRR abs/2402.03345 (2024) - [i56]Paul Krzakala, Junjie Yang, Rémi Flamary, Florence d'Alché-Buc, Charlotte Laclau, Matthieu Labeau:
End-to-end Supervised Prediction of Arbitrary-size Graphs with Partially-Masked Fused Gromov-Wasserstein Matching. CoRR abs/2402.12269 (2024) - [i55]Yanis Lalou, Théo Gnassounou, Antoine Collas, Antoine de Mathelin, Oleksii Kachaiev, Ambroise Odonnat, Alexandre Gramfort, Thomas Moreau, Rémi Flamary:
SKADA-Bench: Benchmarking Unsupervised Domain Adaptation Methods with Realistic Validation. CoRR abs/2407.11676 (2024) - [i54]Théo Gnassounou, Antoine Collas, Rémi Flamary, Karim Lounici, Alexandre Gramfort:
Multi-Source and Test-Time Domain Adaptation on Multivariate Signals using Spatio-Temporal Monge Alignment. CoRR abs/2407.14303 (2024) - 2023
- [c46]Quang Huy Tran, Hicham Janati, Nicolas Courty, Rémi Flamary, Ievgen Redko, Pinar Demetci
, Ritambhara Singh:
Unbalanced CO-optimal Transport. AAAI 2023: 10006-10016 - [c45]Antoine Collas, Titouan Vayer, Rémi Flamary, Arnaud Breloy:
Entropic Wasserstein Component Analysis. MLSP 2023: 1-6 - [c44]Hugues Van Assel, Titouan Vayer, Rémi Flamary, Nicolas Courty:
SNEkhorn: Dimension Reduction with Symmetric Entropic Affinities. NeurIPS 2023 - [c43]Théo Gnassounou, Rémi Flamary, Alexandre Gramfort:
Convolution Monge Mapping Normalization for learning on sleep data. NeurIPS 2023 - [i53]Antoine Collas, Titouan Vayer, Rémi Flamary, Arnaud Breloy:
Entropic Wasserstein Component Analysis. CoRR abs/2303.05119 (2023) - [i52]Hugues Van Assel, Titouan Vayer, Rémi Flamary, Nicolas Courty:
SNEkhorn: Dimension Reduction with Symmetric Entropic Affinities. CoRR abs/2305.13797 (2023) - [i51]Théo Gnassounou, Rémi Flamary, Alexandre Gramfort:
Convolutional Monge Mapping Normalization for learning on biosignals. CoRR abs/2305.18831 (2023) - [i50]Eloi Tanguy, Rémi Flamary, Julie Delon:
Properties of Discrete Sliced Wasserstein Losses. CoRR abs/2307.10352 (2023) - [i49]Hugues Van Assel, Titouan Vayer, Rémi Flamary, Nicolas Courty:
Optimal Transport with Adaptive Regularisation. CoRR abs/2310.02925 (2023) - [i48]Hugues Van Assel, Cédric Vincent-Cuaz, Titouan Vayer, Rémi Flamary, Nicolas Courty:
Interpolating between Clustering and Dimensionality Reduction with Gromov-Wasserstein. CoRR abs/2310.03398 (2023) - 2022
- [j20]Alain Rakotomamonjy, Rémi Flamary, Gilles Gasso, M. El Alaya, Maxime Berar, Nicolas Courty:
Optimal transport for conditional domain matching and label shift. Mach. Learn. 111(5): 1651-1670 (2022) - [j19]Kilian Fatras, Bharath Bhushan Damodaran, Sylvain Lobry, Rémi Flamary, Devis Tuia, Nicolas Courty:
Wasserstein Adversarial Regularization for Learning With Label Noise. IEEE Trans. Pattern Anal. Mach. Intell. 44(10): 7296-7306 (2022) - [j18]Jean-Christophe Burnel, Kilian Fatras, Rémi Flamary, Nicolas Courty:
Generating Natural Adversarial Remote Sensing Images. IEEE Trans. Geosci. Remote. Sens. 60: 1-14 (2022) - [j17]Titouan Vayer, Romain Tavenard, Laetitia Chapel, Rémi Flamary, Nicolas Courty, Yann Soullard:
Time Series Alignment with Global Invariances. Trans. Mach. Learn. Res. 2022 (2022) - [c42]Alain Rakotomamonjy, Rémi Flamary, Joseph Salmon, Gilles Gasso:
Convergent Working Set Algorithm for Lasso with Non-Convex Sparse Regularizers. AISTATS 2022: 5196-5211 - [c41]Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty:
Semi-relaxed Gromov-Wasserstein divergence and applications on graphs. ICLR 2022 - [c40]Luc Brogat-Motte, Rémi Flamary, Céline Brouard, Juho Rousu, Florence d'Alché-Buc:
Learning to Predict Graphs with Fused Gromov-Wasserstein Barycenters. ICML 2022: 2321-2335 - [c39]Alexis Thual, Quang Huy Tran, Tatiana Zemskova, Nicolas Courty, Rémi Flamary, Stanislas Dehaene, Bertrand Thirion:
Aligning individual brains with fused unbalanced Gromov Wasserstein. NeurIPS 2022 - [c38]Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty:
Template based Graph Neural Network with Optimal Transport Distances. NeurIPS 2022 - [c37]Rosanna Turrisi, Rémi Flamary, Alain Rakotomamonjy, Massimiliano Pontil:
Multi-source domain adaptation via weighted joint distributions optimal transport. UAI 2022: 1970-1980 - [i47]Luc Brogat-Motte, Rémi Flamary, Céline Brouard, Juho Rousu, Florence d'Alché-Buc:
Learning to Predict Graphs with Fused Gromov-Wasserstein Barycenters. CoRR abs/2202.03813 (2022) - [i46]Dimitri Bouche, Rémi Flamary, Florence d'Alché-Buc, Riwal Plougonven, Marianne Clausel, Jordi Badosa, Philippe Drobinski:
Wind power predictions from nowcasts to 4-hour forecasts: a learning approach with variable selection. CoRR abs/2204.09362 (2022) - [i45]Quang Huy Tran, Hicham Janati, Nicolas Courty, Rémi Flamary, Ievgen Redko, Pinar Demetci, Ritambhara Singh:
Unbalanced CO-Optimal Transport. CoRR abs/2205.14923 (2022) - [i44]Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty:
Template based Graph Neural Network with Optimal Transport Distances. CoRR abs/2205.15733 (2022) - 2021
- [j16]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, Hicham Janati, Alain Rakotomamonjy, Ievgen Redko, Antoine Rolet, Antony Schutz, Vivien Seguy, Danica J. Sutherland, Romain Tavenard, Alexander Tong, Titouan Vayer:
POT: Python Optimal Transport. J. Mach. Learn. Res. 22: 78:1-78:8 (2021) - [c36]Kilian Fatras, Thibault Séjourné, Rémi Flamary, Nicolas Courty:
Unbalanced minibatch Optimal Transport; applications to Domain Adaptation. ICML 2021: 3186-3197 - [c35]Cédric Vincent-Cuaz, Titouan Vayer, Rémi Flamary, Marco Corneli, Nicolas Courty:
Online Graph Dictionary Learning. ICML 2021: 10564-10574 - [c34]Laetitia Chapel, Rémi Flamary, Haoran Wu, Cédric Févotte, Gilles Gasso:
Unbalanced Optimal Transport through Non-negative Penalized Linear Regression. NeurIPS 2021: 23270-23282 - [i43]Kilian Fatras, Younes Zine, Szymon Majewski, Rémi Flamary, Rémi Gribonval, Nicolas Courty:
Minibatch optimal transport distances; analysis and applications. CoRR abs/2101.01792 (2021) - [i42]Cédric Vincent-Cuaz, Titouan Vayer, Rémi Flamary, Marco Corneli, Nicolas Courty:
Online Graph Dictionary Learning. CoRR abs/2102.06555 (2021) - [i41]Kilian Fatras, Thibault Séjourné, Nicolas Courty, Rémi Flamary:
Unbalanced minibatch Optimal Transport; applications to Domain Adaptation. CoRR abs/2103.03606 (2021) - [i40]Laetitia Chapel, Rémi Flamary, Haoran Wu, Cédric Févotte, Gilles Gasso:
Unbalanced Optimal Transport through Non-negative Penalized Linear Regression. CoRR abs/2106.04145 (2021) - [i39]Quang Huy Tran, Hicham Janati, Ievgen Redko, Rémi Flamary, Nicolas Courty:
Factored couplings in multi-marginal optimal transport via difference of convex programming. CoRR abs/2110.00629 (2021) - [i38]Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty:
Semi-relaxed Gromov Wasserstein divergence with applications on graphs. CoRR abs/2110.02753 (2021) - 2020
- [j15]Titouan Vayer, Laetitia Chapel, Rémi Flamary, Romain Tavenard, Nicolas Courty:
Fused Gromov-Wasserstein Distance for Structured Objects. Algorithms 13(9): 212 (2020) - [j14]Bharath Bhushan Damodaran, Rémi Flamary, Vivien Seguy, Nicolas Courty:
An Entropic Optimal Transport loss for learning deep neural networks under label noise in remote sensing images. Comput. Vis. Image Underst. 191: 102863 (2020) - [c33]Diego Marcos, Ruth Fong, Sylvain Lobry, Rémi Flamary, Nicolas Courty, Devis Tuia:
Contextual Semantic Interpretability. ACCV (4) 2020: 351-368 - [c32]Kilian Fatras, Younes Zine, Rémi Flamary, Rémi Gribonval, Nicolas Courty:
Learning with minibatch Wasserstein : asymptotic and gradient properties. AISTATS 2020: 2131-2141 - [c31]Titouan Vayer, Ievgen Redko, Rémi Flamary, Nicolas Courty:
CO-Optimal Transport. NeurIPS 2020 - [i37]Ievgen Redko, Titouan Vayer, Rémi Flamary, Nicolas Courty:
CO-Optimal Transport. CoRR abs/2002.03731 (2020) - [i36]Titouan Vayer, Laetitia Chapel, Nicolas Courty, Rémi Flamary, Yann Soullard, Romain Tavenard:
Time Series Alignment with Global Invariances. CoRR abs/2002.03848 (2020) - [i35]Alain Rakotomamonjy, Rémi Flamary, Gilles Gasso, Mokhtar Z. Alaya, Maxime Berar, Nicolas Courty:
Match and Reweight Strategy for Generalized Target Shift. CoRR abs/2006.08161 (2020) - [i34]Rosanna Turrisi, Rémi Flamary, Alain Rakotomamonjy, Massimiliano Pontil:
Multi-source Domain Adaptation via Weighted Joint Distributions Optimal Transport. CoRR abs/2006.12938 (2020) - [i33]Alain Rakotomamonjy, Rémi Flamary, Gilles Gasso, Joseph Salmon:
Provably Convergent Working Set Algorithm for Non-Convex Regularized Regression. CoRR abs/2006.13533 (2020) - [i32]Xuhong Li, Yves Grandvalet, Rémi Flamary, Nicolas Courty, Dejing Dou:
Representation Transfer by Optimal Transport. CoRR abs/2007.06737 (2020) - [i31]Diego Marcos, Ruth Fong, Sylvain Lobry, Rémi Flamary, Nicolas Courty, Devis Tuia:
Contextual Semantic Interpretability. CoRR abs/2009.08720 (2020)
2010 – 2019
- 2019
- [j13]Ibrahim El Khalil Harrane, Rémi Flamary, Cédric Richard:
On Reducing the Communication Cost of the Diffusion LMS Algorithm. IEEE Trans. Signal Inf. Process. over Networks 5(1): 100-112 (2019) - [c30]Ievgen Redko, Nicolas Courty, Rémi Flamary, Devis Tuia:
Optimal Transport for Multi-source Domain Adaptation under Target Shift. AISTATS 2019: 849-858 - [c29]Titouan Vayer, Nicolas Courty, Romain Tavenard, Laetitia Chapel, Rémi Flamary:
Optimal Transport for structured data with application on graphs. ICML 2019: 6275-6284 - [c28]Titouan Vayer, Rémi Flamary, Nicolas Courty, Romain Tavenard, Laetitia Chapel:
Sliced Gromov-Wasserstein. NeurIPS 2019: 14726-14736 - [i30]Bharath Bhushan Damodaran, Kilian Fatras, Sylvain Lobry, Rémi Flamary, Devis Tuia, Nicolas Courty:
Pushing the right boundaries matters! Wasserstein Adversarial Training for Label Noise. CoRR abs/1904.03936 (2019) - [i29]Titouan Vayer, Rémi Flamary, Romain Tavenard, Laetitia Chapel, Nicolas Courty:
Sliced Gromov-Wasserstein. CoRR abs/1905.10124 (2019) - [i28]Rémi Flamary, Karim Lounici, André Ferrari:
Concentration bounds for linear Monge mapping estimation and optimal transport domain adaptation. CoRR abs/1905.10155 (2019) - [i27]Laurent Dragoni, Rémi Flamary, Karim Lounici, Patricia Reynaud-Bouret:
Large scale Lasso with windowed active set for convolutional spike sorting. CoRR abs/1906.12077 (2019) - [i26]Kilian Fatras, Younes Zine, Rémi Flamary, Rémi Gribonval, Nicolas Courty:
Learning with minibatch Wasserstein : asymptotic and gradient properties. CoRR abs/1910.04091 (2019) - 2018
- [j12]Rémi Flamary, Marco Cuturi, Nicolas Courty, Alain Rakotomamonjy:
Wasserstein discriminant analysis. Mach. Learn. 107(12): 1923-1945 (2018) - [c27]Bharath Bhushan Damodaran, Benjamin Kellenberger, Rémi Flamary, Devis Tuia, Nicolas Courty:
DeepJDOT: Deep Joint Distribution Optimal Transport for Unsupervised Domain Adaptation. ECCV (4) 2018: 467-483 - [c26]Nicolas Courty, Rémi Flamary, Mélanie Ducoffe:
Learning Wasserstein Embeddings. ICLR (Poster) 2018 - [c25]Vivien Seguy, Bharath Bhushan Damodaran, Rémi Flamary, Nicolas Courty, Antoine Rolet, Mathieu Blondel:
Large Scale Optimal Transport and Mapping Estimation. ICLR (Poster) 2018 - [i25]Alain Rakotomamonjy, Abraham Traoré, Maxime Berar, Rémi Flamary, Nicolas Courty:
Wasserstein Distance Measure Machines. CoRR abs/1803.00250 (2018) - [i24]Bharath Bhushan Damodaran, Benjamin Kellenberger, Rémi Flamary, Devis Tuia, Nicolas Courty:
DeepJDOT: Deep Joint distribution optimal transport for unsupervised domain adaptation. CoRR abs/1803.10081 (2018) - [i23]Titouan Vayer, Laetitia Chapel, Rémi Flamary, Romain Tavenard, Nicolas Courty:
Optimal Transport for structured data. CoRR abs/1805.09114 (2018) - [i22]Bharath Bhushan Damodaran, Rémi Flamary, Vivien Seguy, Nicolas Courty:
An Entropic Optimal Transport Loss for Learning Deep Neural Networks under Label Noise in Remote Sensing Images. CoRR abs/1810.01163 (2018) - [i21]Titouan Vayer, Laetitia Chapel, Rémi Flamary, Romain Tavenard, Nicolas Courty:
Fused Gromov-Wasserstein distance for structured objects: theoretical foundations and mathematical properties. CoRR abs/1811.02834 (2018) - 2017
- [j11]Nicolas Courty, Rémi Flamary, Devis Tuia, Alain Rakotomamonjy:
Optimal Transport for Domain Adaptation. IEEE Trans. Pattern Anal. Mach. Intell. 39(9): 1853-1865 (2017) - [c24]Rita Ammanouil, André Ferrari, Rémi Flamary, Chiara Ferrari, David Mary:
Multi-frequency image reconstruction for radio-interferometry with self-tuned regularization parameters. EUSIPCO 2017: 1435-1439 - [c23]Rahul Mourya, André Ferrari, Rémi Flamary, Pascal Bianchi, Cédric Richard:
Distributed approach for deblurring large images with shift-variant blur. EUSIPCO 2017: 2463-2470 - [c22]Rémi Flamary:
Astronomical image reconstruction with convolutional neural networks. EUSIPCO 2017: 2468-2472 - [c21]Nicolas Courty, Rémi Flamary, Amaury Habrard, Alain Rakotomamonjy:
Joint distribution optimal transportation for domain adaptation. NIPS 2017: 3730-3739 - [i20]Rita Ammanouil, André Ferrari, Rémi Flamary, Chiara Ferrari, David Mary:
Multi-frequency image reconstruction for radio-interferometry with self-tuned regularization parameters. CoRR abs/1703.03608 (2017) - [i19]Nicolas Courty, Rémi Flamary, Amaury Habrard, Alain Rakotomamonjy:
Joint Distribution Optimal Transportation for Domain Adaptation. CoRR abs/1705.08848 (2017) - [i18]Nicolas Courty, Rémi Flamary, Mélanie Ducoffe:
Learning Wasserstein Embeddings. CoRR abs/1710.07457 (2017) - [i17]Ibrahim El Khalil Harrane, Rémi Flamary, Cédric Richard:
On reducing the communication cost of the diffusion LMS algorithm. CoRR abs/1711.11423 (2017) - 2016
- [j10]Devis Tuia, Rémi Flamary, Michel Barlaud:
Nonconvex Regularization in Remote Sensing. IEEE Trans. Geosci. Remote. Sens. 54(11): 6470-6480 (2016) - [j9]Alain Rakotomamonjy, Rémi Flamary, Gilles Gasso:
DC Proximal Newton for Nonconvex Optimization Problems. IEEE Trans. Neural Networks Learn. Syst. 27(3): 636-647 (2016) - [c20]Ibrahim El Khalil Harrane, Rémi Flamary, Cédric Richard:
Doubly compressed diffusion LMS over adaptive networks. ACSSC 2016: 987-991 - [c19]Ibrahim El Khalil Harrane, Rémi Flamary, Cédric Richard:
Toward privacy-preserving diffusion strategies for adaptation and learning over networks. EUSIPCO 2016: 1513-1517 - [c18]Nicolas Courty, Rémi Flamary, Devis Tuia, Thomas Corpetti:
Optimal transport for data fusion in remote sensing. IGARSS 2016: 3571-3574 - [c17]Rémi Flamary, Cédric Févotte, Nicolas Courty, Valentin Emiya:
Optimal spectral transportation with application to music transcription. NIPS 2016: 703-711 - [c16]Michaël Perrot, Nicolas Courty, Rémi Flamary, Amaury Habrard:
Mapping Estimation for Discrete Optimal Transport. NIPS 2016: 4197-4205 - [c15]Sina Nakhostin, Nicolas Courty, Rémi Flamary, Thomas Corpetti:
Supervised planetary unmixing with optimal transport. WHISPERS 2016: 1-5 - [i16]Devis Tuia, Rémi Flamary, Nicolas Courty:
Multiclass feature learning for hyperspectral image classification: sparse and hierarchical solutions. CoRR abs/1606.07279 (2016) - [i15]Rémi Flamary, Alain Rakotomamonjy, Gilles Gasso:
Importance sampling strategy for non-convex randomized block-coordinate descent. CoRR abs/1606.07286 (2016) - [i14]Devis Tuia, Rémi Flamary, Michel Barlaud:
Non-convex regularization in remote sensing. CoRR abs/1606.07289 (2016) - [i13]Rémi Flamary, Marco Cuturi, Nicolas Courty, Alain Rakotomamonjy:
Wasserstein Discriminant Analysis. CoRR abs/1608.08063 (2016) - [i12]Rémi Flamary, Cédric Févotte, Nicolas Courty, Valentin Emiya:
Optimal spectral transportation with application to music transcription. CoRR abs/1609.09799 (2016) - [i11]Rémi Flamary:
Astronomical image reconstruction with convolutional neural networks. CoRR abs/1612.04526 (2016) - 2015
- [j8]Rémi Flamary, Mathieu Fauvel, Mauro Dalla Mura, Silvia Valero:
Analysis of Multitemporal Classification Techniques for Forecasting Image Time Series. IEEE Geosci. Remote. Sens. Lett. 12(5): 953-957 (2015) - [c14]Rémi Flamary, Alain Rakotomamonjy, Gilles Gasso:
Importance sampling strategy for non-convex randomized block-coordinate descent. CAMSAP 2015: 301-304 - [c13]Devis Tuia, Rémi Flamary, Michel Barlaud:
To be or not to be convex? A study on regularization in hyperspectral image classification. IGARSS 2015: 4947-4950 - [c12]Devis Tuia, Rémi Flamary, Alain Rakotomamonjy, Nicolas Courty:
Multitemporal classification without new labels: A solution with optimal transport. MultiTemp 2015: 1-4 - [i10]Alain Rakotomamonjy, Rémi Flamary, Gilles Gasso:
DC Proximal Newton for Non-Convex Optimization Problems. CoRR abs/1507.00438 (2015) - [i9]Léa Laporte, Rémi Flamary, Stéphane Canu, Sébastien Déjean, Josiane Mothe:
Non-convex Regularizations for Feature Selection in Ranking With Sparse SVM. CoRR abs/1507.00500 (2015) - [i8]André Ferrari, David Mary, Rémi Flamary, Cédric Richard:
Distributed image reconstruction for very large arrays in radio astronomy. CoRR abs/1507.00501 (2015) - [i7]Nicolas Courty, Rémi Flamary, Devis Tuia, Alain Rakotomamonjy:
Optimal Transport for Domain Adaptation. CoRR abs/1507.00504 (2015) - [i6]Alain Rakotomamonjy, Rémi Flamary, Nicolas Courty:
Generalized conditional gradient: analysis of convergence and applications. CoRR abs/1510.06567 (2015) - 2014
- [j7]Rémi Flamary, Nisrine Jrad, Ronald Phlypo, Marco Congedo, Alain Rakotomamonjy:
Mixed-Norm Regularization for Brain Decoding. Comput. Math. Methods Medicine 2014: 317056:1-317056:13 (2014) - [j6]Devis Tuia, Michele Volpi, Mauro Dalla Mura, Alain Rakotomamonjy, Rémi Flamary:
Automatic Feature Learning for Spatio-Spectral Image Classification With Sparse SVM. IEEE Trans. Geosci. Remote. Sens. 52(10): 6062-6074 (2014) - [j5]Emilie Niaf, Rémi Flamary, Olivier Rouvière, Carole Lartizien, Stéphane Canu:
Kernel-Based Learning From Both Qualitative and Quantitative Labels: Application to Prostate Cancer Diagnosis Based on Multiparametric MR Imaging. IEEE Trans. Image Process. 23(3): 979-991 (2014) - [j4]Léa Laporte, Rémi Flamary, Stéphane Canu, Sébastien Déjean, Josiane Mothe:
Nonconvex Regularizations for Feature Selection in Ranking With Sparse SVM. IEEE Trans. Neural Networks Learn. Syst. 25(6): 1118-1130 (2014) - [c11]Aurelie Boisbunon, Rémi Flamary, Alain Rakotomamonjy:
Active set strategy for high-dimensional non-convex sparse optimization problems. ICASSP 2014: 1517-1521 - [c10]Emilie Niaf, Rémi Flamary, Alain Rakotomamonjy, Olivier Rouvière, Carole Lartizien:
SVM with feature selection and smooth prediction in images: Application to CAD of prostate cancer. ICIP 2014: 2246-2250 - [c9]Jérôme Lehaire, Rémi Flamary, Olivier Rouvière, Carole Lartizien:
Computer-aided diagnostic system for prostate cancer detection and characterization combining learned dictionaries and supervised classification. ICIP 2014: 2251-2255 - [c8]André Ferrari, David Mary, Rémi Flamary, Cédric Richard:
Distributed image reconstruction for very large arrays in radio astronomy. SAM 2014: 389-392 - [c7]Nicolas Courty, Rémi Flamary, Devis Tuia:
Domain Adaptation with Regularized Optimal Transport. ECML/PKDD (1) 2014: 274-289 - [i5]Rémi Flamary, Nisrine Jrad, Ronald Phlypo, Marco Congedo, Alain Rakotomamonjy:
Mixed-norm Regularization for Brain Decoding. CoRR abs/1403.3628 (2014) - 2013
- [j3]Alain Rakotomamonjy, Rémi Flamary, Florian Yger:
Learning with infinitely many features. Mach. Learn. 91(1): 43-66 (2013) - [c6]Wei Gao, Jie Chen, Cédric Richard, Jianguo Huang, Rémi Flamary:
Kernel LMS algorithm with forward-backward splitting for dictionary learning. ICASSP 2013: 5735-5739 - [c5]Devis Tuia, Michele Volpi, Mauro Dalla Mura, Alain Rakotomamonjy, Rémi Flamary:
Create the relevant spatial filterbank in the hyperspectral jungle. IGARSS 2013: 2172-2175 - 2012
- [j2]Rémi Flamary, Devis Tuia, Benjamin Labbé, Gustavo Camps-Valls, Alain Rakotomamonjy:
Large Margin Filtering. IEEE Trans. Signal Process. 60(2): 648-659 (2012) - [c4]Devis Tuia, Mauro Dalla Mura, Michele Volpi, Rémi Flamary, Alain Rakotomamonjy:
Discovering relevant spatial filterbanks for VHR image classification. ICPR 2012: 3212-3215 - 2011
- [b1]Rémi Flamary:
Apprentissage statistique pour le signal: applications aux interfaces cerveau-machine. (Machine learning for signal processing : applications to Brain Computer Interfaces). University of Rouen, France, 2011 - [j1]Alain Rakotomamonjy, Rémi Flamary, Gilles Gasso, Stéphane Canu:
ellp-ellq Penalty for Sparse Linear and Sparse Multiple Kernel Multitask Learning. IEEE Trans. Neural Networks 22(8): 1307-1320 (2011) - [c3]Rémi Flamary, Xavier Anguera, Nuria Oliver:
Spoken WordCloud: Clustering recurrent patterns in speech. CBMI 2011: 133-138 - [c2]Rémi Flamary, Florian Yger, Alain Rakotomamonjy:
Selecting from an infinite set of features in SVM. ESANN 2011 - [i4]Rémi Flamary, Alain Rakotomamonjy:
Decoding finger movements from ECoG signals using switching linear models. CoRR abs/1106.3395 (2011) - [i3]Rémi Flamary, Benjamin Labbé, Alain Rakotomamonjy:
Large margin filtering for signal sequence labeling. CoRR abs/1106.3396 (2011) - [i2]Emilie Niaf, Rémi Flamary, Carole Lartizien, Stéphane Canu:
Handling uncertainties in SVM classification. CoRR abs/1106.3397 (2011) - 2010
- [c1]Rémi Flamary, Benjamin Labbé, Alain Rakotomamonjy:
Large margin filtering for Signal Sequence Labeling. ICASSP 2010: 1974-1977 - [i1]Rémi Flamary, Benjamin Labbé, Alain Rakotomamonjy:
Filtrage vaste marge pour l'étiquetage séquentiel à noyaux de signaux. CoRR abs/1007.0824 (2010)
Coauthor Index
[i58] [c46] [c44] [i52] [i49] [i48] [j20] [j19] [j18] [j17] [c41] [c39] [c38] [i45] [i44] [j16] [c36] [c35] [i43] [i42] [i41] [i39] [i38] [j15] [j14] [c33] [c32] [c31] [i37] [i36] [i35] [i32] [i31] [c30] [c29] [c28] [i30] [i29] [i26] [j12] [c27] [c26] [c25] [i25] [i24] [i23] [i22] [i21] [j11] [c21] [i19] [i18] [c18] [c17] [c16] [c15] [i16] [i13] [i12] [c12] [i7] [i6] [c7]
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Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
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OpenAlex data
Load additional information about publications from 
.
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last updated on 2024-10-07 21:22 CEST by the dblp team
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