Rémi Flamary

Orcid: 0000-0002-4212-6627

According to our database1, Rémi Flamary authored at least 95 papers between 2010 and 2024.

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Bibliography

2024
End-to-end Supervised Prediction of Arbitrary-size Graphs with Partially-Masked Fused Gromov-Wasserstein Matching.
CoRR, 2024

Weakly supervised covariance matrices alignment through Stiefel matrices estimation for MEG applications.
CoRR, 2024

Distributional Reduction: Unifying Dimensionality Reduction and Clustering with Gromov-Wasserstein Projection.
CoRR, 2024

2023
Interpolating between Clustering and Dimensionality Reduction with Gromov-Wasserstein.
CoRR, 2023

Optimal Transport with Adaptive Regularisation.
CoRR, 2023

Properties of Discrete Sliced Wasserstein Losses.
CoRR, 2023

Convolutional Monge Mapping Normalization for learning on biosignals.
CoRR, 2023

Convolution Monge Mapping Normalization for learning on sleep data.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

SNEkhorn: Dimension Reduction with Symmetric Entropic Affinities.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Entropic Wasserstein Component Analysis.
Proceedings of the 33rd IEEE International Workshop on Machine Learning for Signal Processing, 2023

Unbalanced CO-optimal Transport.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Time Series Alignment with Global Invariances.
Trans. Mach. Learn. Res., 2022

Generating Natural Adversarial Remote Sensing Images.
IEEE Trans. Geosci. Remote. Sens., 2022

Wasserstein Adversarial Regularization for Learning With Label Noise.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Optimal transport for conditional domain matching and label shift.
Mach. Learn., 2022

Wind power predictions from nowcasts to 4-hour forecasts: a learning approach with variable selection.
CoRR, 2022

Multi-source domain adaptation via weighted joint distributions optimal transport.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Template based Graph Neural Network with Optimal Transport Distances.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Aligning individual brains with fused unbalanced Gromov Wasserstein.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning to Predict Graphs with Fused Gromov-Wasserstein Barycenters.
Proceedings of the International Conference on Machine Learning, 2022

Semi-relaxed Gromov-Wasserstein divergence and applications on graphs.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Convergent Working Set Algorithm for Lasso with Non-Convex Sparse Regularizers.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
POT: Python Optimal Transport.
J. Mach. Learn. Res., 2021

Semi-relaxed Gromov Wasserstein divergence with applications on graphs.
CoRR, 2021

Factored couplings in multi-marginal optimal transport via difference of convex programming.
CoRR, 2021

Minibatch optimal transport distances; analysis and applications.
CoRR, 2021

Unbalanced Optimal Transport through Non-negative Penalized Linear Regression.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Online Graph Dictionary Learning.
Proceedings of the 38th International Conference on Machine Learning, 2021

Unbalanced minibatch Optimal Transport; applications to Domain Adaptation.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
An Entropic Optimal Transport loss for learning deep neural networks under label noise in remote sensing images.
Comput. Vis. Image Underst., 2020

Representation Transfer by Optimal Transport.
CoRR, 2020

Provably Convergent Working Set Algorithm for Non-Convex Regularized Regression.
CoRR, 2020

Match and Reweight Strategy for Generalized Target Shift.
CoRR, 2020

Fused Gromov-Wasserstein Distance for Structured Objects.
Algorithms, 2020

CO-Optimal Transport.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning with minibatch Wasserstein : asymptotic and gradient properties.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Contextual Semantic Interpretability.
Proceedings of the Computer Vision - ACCV 2020 - 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30, 2020

2019
On Reducing the Communication Cost of the Diffusion LMS Algorithm.
IEEE Trans. Signal Inf. Process. over Networks, 2019

Large scale Lasso with windowed active set for convolutional spike sorting.
CoRR, 2019

Concentration bounds for linear Monge mapping estimation and optimal transport domain adaptation.
CoRR, 2019

Pushing the right boundaries matters! Wasserstein Adversarial Training for Label Noise.
CoRR, 2019

Sliced Gromov-Wasserstein.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Optimal Transport for structured data with application on graphs.
Proceedings of the 36th International Conference on Machine Learning, 2019

Optimal Transport for Multi-source Domain Adaptation under Target Shift.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Wasserstein discriminant analysis.
Mach. Learn., 2018

Fused Gromov-Wasserstein distance for structured objects: theoretical foundations and mathematical properties.
CoRR, 2018

Optimal Transport for structured data.
CoRR, 2018

Wasserstein Distance Measure Machines.
CoRR, 2018

Large Scale Optimal Transport and Mapping Estimation.
Proceedings of the 6th International Conference on Learning Representations, 2018

Learning Wasserstein Embeddings.
Proceedings of the 6th International Conference on Learning Representations, 2018

DeepJDOT: Deep Joint Distribution Optimal Transport for Unsupervised Domain Adaptation.
Proceedings of the Computer Vision - ECCV 2018, 2018

2017
Optimal Transport for Domain Adaptation.
IEEE Trans. Pattern Anal. Mach. Intell., 2017

Joint distribution optimal transportation for domain adaptation.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Distributed approach for deblurring large images with shift-variant blur.
Proceedings of the 25th European Signal Processing Conference, 2017

Astronomical image reconstruction with convolutional neural networks.
Proceedings of the 25th European Signal Processing Conference, 2017

Multi-frequency image reconstruction for radio-interferometry with self-tuned regularization parameters.
Proceedings of the 25th European Signal Processing Conference, 2017

2016
DC Proximal Newton for Nonconvex Optimization Problems.
IEEE Trans. Neural Networks Learn. Syst., 2016

Nonconvex Regularization in Remote Sensing.
IEEE Trans. Geosci. Remote. Sens., 2016

Multiclass feature learning for hyperspectral image classification: sparse and hierarchical solutions.
CoRR, 2016

Non-convex regularization in remote sensing.
CoRR, 2016

Supervised planetary unmixing with optimal transport.
Proceedings of the 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2016

Mapping Estimation for Discrete Optimal Transport.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Optimal spectral transportation with application to music transcription.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Optimal transport for data fusion in remote sensing.
Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium, 2016

Toward privacy-preserving diffusion strategies for adaptation and learning over networks.
Proceedings of the 24th European Signal Processing Conference, 2016

Doubly compressed diffusion LMS over adaptive networks.
Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016

2015
Analysis of Multitemporal Classification Techniques for Forecasting Image Time Series.
IEEE Geosci. Remote. Sens. Lett., 2015

DC Proximal Newton for Non-Convex Optimization Problems.
CoRR, 2015

Generalized conditional gradient: analysis of convergence and applications.
CoRR, 2015

Non-convex Regularizations for Feature Selection in Ranking With Sparse SVM.
CoRR, 2015

Multitemporal classification without new labels: A solution with optimal transport.
Proceedings of the 8th International Workshop on the Analysis of Multitemporal Remote Sensing Images, 2015

To be or not to be convex? A study on regularization in hyperspectral image classification.
Proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium, 2015

Importance sampling strategy for non-convex randomized block-coordinate descent.
Proceedings of the 6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2015

2014
Nonconvex Regularizations for Feature Selection in Ranking With Sparse SVM.
IEEE Trans. Neural Networks Learn. Syst., 2014

Kernel-Based Learning From Both Qualitative and Quantitative Labels: Application to Prostate Cancer Diagnosis Based on Multiparametric MR Imaging.
IEEE Trans. Image Process., 2014

Automatic Feature Learning for Spatio-Spectral Image Classification With Sparse SVM.
IEEE Trans. Geosci. Remote. Sens., 2014

Mixed-Norm Regularization for Brain Decoding.
Comput. Math. Methods Medicine, 2014

Domain Adaptation with Regularized Optimal Transport.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

Distributed image reconstruction for very large arrays in radio astronomy.
Proceedings of the IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, 2014

SVM with feature selection and smooth prediction in images: Application to CAD of prostate cancer.
Proceedings of the 2014 IEEE International Conference on Image Processing, 2014

Computer-aided diagnostic system for prostate cancer detection and characterization combining learned dictionaries and supervised classification.
Proceedings of the 2014 IEEE International Conference on Image Processing, 2014

Active set strategy for high-dimensional non-convex sparse optimization problems.
Proceedings of the IEEE International Conference on Acoustics, 2014

2013
Learning with infinitely many features.
Mach. Learn., 2013

Create the relevant spatial filterbank in the hyperspectral jungle.
Proceedings of the 2013 IEEE International Geoscience and Remote Sensing Symposium, 2013

Kernel LMS algorithm with forward-backward splitting for dictionary learning.
Proceedings of the IEEE International Conference on Acoustics, 2013

2012
Large Margin Filtering.
IEEE Trans. Signal Process., 2012

Discovering relevant spatial filterbanks for VHR image classification.
Proceedings of the 21st International Conference on Pattern Recognition, 2012

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

ell<sub>p</sub>-ell<sub>q</sub> Penalty for Sparse Linear and Sparse Multiple Kernel Multitask Learning.
IEEE Trans. Neural Networks, 2011

Handling uncertainties in SVM classification
CoRR, 2011

Decoding finger movements from ECoG signals using switching linear models
CoRR, 2011

Selecting from an infinite set of features in SVM.
Proceedings of the 19th European Symposium on Artificial Neural Networks, 2011

Spoken WordCloud: Clustering recurrent patterns in speech.
Proceedings of the 9th International Workshop on Content-Based Multimedia Indexing, 2011

2010
Filtrage vaste marge pour l'étiquetage séquentiel à noyaux de signaux
CoRR, 2010

Large margin filtering for Signal Sequence Labeling.
Proceedings of the IEEE International Conference on Acoustics, 2010


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