Frame Kernels for Learning. - Alain Rakotomamonjy; Stéphane Canu (ICANN, 2002)

Comparaison de stratégies de discrimination de masses de véhicules automobiles. - Alain Rakotomamonjy; Rodolphe Le Riche; David Gualandris; Stéphane Canu (Rev. d'Intelligence Artif., 2002)

Variable Selection Using SVM-based Criteria. - Alain Rakotomamonjy (J. Mach. Learn. Res., 2003)

Generic target recognition. - Christophe Rosenberger; Alain Rakotomamonjy; Bruno Emile (EUSIPCO, 2004)

Optimizing Area Under Roc Curve with SVMs. - Alain Rakotomamonjy (ROCAI, 2004)

Evaluation of the quality of ultrasound image compression by fusion of criteria with a support vector machine. - Cécile Delgorge; Christophe Rosenberger; Alain Rakotomamonjy; Gérard Poisson; Pierre Vieyres (EUSIPCO, 2005)

Ensemble of SVMs for Improving Brain Computer Interface P300 Speller Performances. - Alain Rakotomamonjy; Vincent Guigue; Grégory Mallet; Victor Alvarado (ICANN (1), 2005)

Segmentation Evaluation Using a Support Vector Machine. - Sébastien Chabrier; Christophe Rosenberger; Hélène Laurent; Alain Rakotomamonjy (ICAPR (1), 2005)

Frames, Reproducing Kernels, Regularization and Learning. - Alain Rakotomamonjy; Stéphane Canu (J. Mach. Learn. Res., 2005)

Object Categorization Using Kernels Combining Graphs and Histograms of Gradients. - Frédéric Suard; Alain Rakotomamonjy; Abdelaziz Bensrhair (ICIAR (2), 2006)

Translation-invariant classification of non-stationary signals. - Vincent Guigue; Alain Rakotomamonjy; Stéphane Canu (Neurocomputing, 2006)

Kernel Basis Pursuit. - Vincent Guigue; Alain Rakotomamonjy; Stéphane Canu (Rev. d'Intelligence Artif., 2006)

Perception d'états affectifs et apprentissage. - Gaëlle Loosli; Sans-Goog Lee; Alain Rakotomamonjy (Rev. d'Intelligence Artif., 2006)

One-class SVM regularization path and comparison with alpha seeding. - Alain Rakotomamonjy; Manuel Davy (ESANN, 2007)

Kernel on Bag of Paths For Measuring Similarity of Shapes. - Frédéric Suard; Alain Rakotomamonjy; Abdelaziz Bensrhair (ESANN, 2007)

More efficiency in multiple kernel learning. - Alain Rakotomamonjy; Francis R. Bach; Stéphane Canu; Yves Grandvalet (ICML, 2007)

A Pedestrian Detector Using Histograms of Oriented Gradients and a Support Vector Machine Classifier. - Massimo Bertozzi; Alberto Broggi; Michael S. Del Rose; Mirko Felisa; Alain Rakotomamonjy; Frédéric Suard (ITSC, 2007)

Analysis of SVM regression bounds for variable ranking. - Alain Rakotomamonjy (Neurocomputing, 2007)

Support Vector Machines with a Reject Option. - Yves Grandvalet; Alain Rakotomamonjy; Joseph Keshet; Stéphane Canu (NIPS, 2008)

BCI Competition III: Dataset II- Ensemble of SVMs for BCI P300 Speller. - Alain Rakotomamonjy; Vincent Guigue (IEEE Trans. Biomed. Eng., 2008)

Recovering sparse signals with a certain family of nonconvex penalties and DC programming. - Gilles Gasso; Alain Rakotomamonjy; Stéphane Canu (IEEE Trans. Signal Process., 2009)

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

Large marginwavelet-based dictionary for signal classification. - Florian Yger; Alain Rakotomamonjy (ICASSP, 2010)

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

Composite kernel learning. - Marie Szafranski; Yves Grandvalet; Alain Rakotomamonjy (Mach. Learn., 2010)

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

A supervised strategy for deep kernel machine. - Florian Yger; Maxime Berar; Gilles Gasso; Alain Rakotomamonjy (ESANN, 2011)

Functional Regularized Least Squares Classication with Operator-valued Kernels. - Hachem Kadri; Asma Rabaoui; Philippe Preux; Emmanuel Duflos; Alain Rakotomamonjy (ICML, 2011)

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

Wavelet kernel learning. - Florian Yger; Alain Rakotomamonjy (Pattern Recognit., 2011)

Apprentissage de dictionnaires d'ondelettes vaste marge pour la classification de signaux et de textures. - Florian Yger; Alain Rakotomamonjy (Rev. d'Intelligence Artif., 2011)

Surveying and comparing simultaneous sparse approximation (or group-lasso) algorithms. - Alain Rakotomamonjy (Signal Process., 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)

Learning geometric combinations of Gaussian kernels with alternating Quasi-Newton algorithm. - David Picard; Nicolas Thome; Matthieu Cord; Alain Rakotomamonjy (ESANN, 2012)

Oblique principal subspace tracking on manifold. - Florian Yger; Maxime Berar; Gilles Gasso; Alain Rakotomamonjy (ICASSP, 2012)

Sparse Support Vector Infinite Push. - Alain Rakotomamonjy (ICML, 2012)

Adaptive Canonical Correlation Analysis Based On Matrix Manifolds. - Florian Yger; Maxime Berar; Gilles Gasso; Alain Rakotomamonjy (ICML, 2012)

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

Multiple Operator-valued Kernel Learning. - Hachem Kadri; Alain Rakotomamonjy; Francis R. Bach; Philippe Preux (NIPS, 2012)

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

Filter bank Kernel Learning for nonstationary signal classification. - Maxime Sangnier; Jérôme Gauthier; Alain Rakotomamonjy (ICASSP, 2013)

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

Functional Regularized Least Squares Classi cation with Operator-valued Kernels - Hachem Kadri; Asma Rabaoui; Philippe Preux; Emmanuel Duflos; Alain Rakotomamonjy (CoRR, 2013)

Applying alternating direction method of multipliers for constrained dictionary learning. - Alain Rakotomamonjy (Neurocomputing, 2013)

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

Direct Optimization of the Dictionary Learning Problem. - Alain Rakotomamonjy (IEEE Trans. Signal Process., 2013)

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

Kernel learning as minimization of the single validation estimate. - Maxime Sangnier; Jérôme Gauthier; Alain Rakotomamonjy (MLSP, 2014)

Scattering features for lung cancer detection in fibered confocal fluorescence microscopy images. - Alain Rakotomamonjy; Caroline Petitjean; Mathieu Salaün; Luc Thiberville (Artif. Intell. Medicine, 2014)

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

ℓp-norm multiple kernel learning with low-rank kernels. - Alain Rakotomamonjy; Sukalpa Chanda (Neurocomputing, 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)

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

More efficient sparsity-inducing algorithms using inexact gradient. - Alain Rakotomamonjy; Sokol Koço; Liva Ralaivola (EUSIPCO, 2015)

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

Early frame-based detection of acoustic scenes. - Maxime Sangnier; Jérôme Gauthier; Alain Rakotomamonjy (WASPAA, 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)

Histogram of gradients of Time-Frequency Representations for Audio scene detection. - Alain Rakotomamonjy; Gilles Gasso (CoRR, 2015)

Greedy methods, randomization approaches and multi-arm bandit algorithms for efficient sparsity-constrained optimization. - Alain Rakotomamonjy; Sokol Koço; Liva Ralaivola (CoRR, 2015)

Filter bank learning for signal classification. - Maxime Sangnier; Jérôme Gauthier; Alain Rakotomamonjy (Signal Process., 2015)

Histogram of Gradients of Time-Frequency Representations for Audio Scene Classification. - Alain Rakotomamonjy; Gilles Gasso (IEEE ACM Trans. Audio Speech Lang. Process., 2015)

Early and Reliable Event Detection Using Proximity Space Representation. - Maxime Sangnier; Jérôme Gauthier; Alain Rakotomamonjy (ICML, 2016)

Operator-valued Kernels for Learning from Functional Response Data. - Hachem Kadri; Emmanuel Duflos; Philippe Preux; Stéphane Canu; Alain Rakotomamonjy; Julien Audiffren (J. Mach. Learn. Res., 2016)

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

Optimal transport Applied to Transfer Learning for P300 Detection. - Nathalie T. H. Gayraud; Alain Rakotomamonjy; Maureen Clerc (GBCIC, 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)

Supervised Representation Learning for Audio Scene Classification. - Alain Rakotomamonjy (IEEE ACM Trans. Audio Speech Lang. Process., 2017)

Editorial: A Successful Year and Looking Forward to 2017 and Beyond. - Haibo He; Robert Haas; Jun Fu; Barbara Hammer; Daniel W. C. Ho; Fakhri Karray; Dhireesha Kudithipudi; José Antonio Lozano 001; Teresa Bernarda Ludermir; Jacek Mandziuk; Stefano Melacci; Antonio Paiva; et al. (IEEE Trans. Neural Networks Learn. Syst., 2017)

Greedy Methods, Randomization Approaches, and Multiarm Bandit Algorithms for Efficient Sparsity-Constrained Optimization. - Alain Rakotomamonjy; Sokol Koço; Liva Ralaivola (IEEE Trans. Neural Networks Learn. Syst., 2017)

Non-Negative Tensor Dictionary Learning. - Abraham Traoré; Maxime Berar; Alain Rakotomamonjy (ESANN, 2018)

Concave Losses for Robust Dictionary Learning. - Rafael Will M. de Araujo; Roberto Hirata; Alain Rakotomamonjy (ICASSP, 2018)

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

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

Screening rules for Lasso with non-convex Sparse Regularizers. - Alain Rakotomamonjy; Gilles Gasso; Joseph Salmon (ICML, 2019)

Screening Sinkhorn Algorithm for Regularized Optimal Transport. - Mokhtar Z. Alaya; Maxime Berar; Gilles Gasso; Alain Rakotomamonjy (NeurIPS, 2019)

Singleshot : a scalable Tucker tensor decomposition. - Abraham Traoré; Maxime Berar; Alain Rakotomamonjy (NeurIPS, 2019)

Online multimodal dictionary learning. - Abraham Traoré; Maxime Berar; Alain Rakotomamonjy (Neurocomputing, 2019)

Partial Trace Regression and Low-Rank Kraus Decomposition. - Hachem Kadri; Stéphane Ayache; Riikka Huusari; Alain Rakotomamonjy; Liva Ralaivola (ICML, 2020)

Non-Aligned Distribution Distance using Metric Measure Embedding and Optimal Transport. - Mokhtar Z. Alaya; Maxime Bérar; Gilles Gasso; Alain Rakotomamonjy (CoRR, 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)

Wasserstein Learning of Determinantal Point Processes. - Lucas Anquetil; Mike Gartrell; Alain Rakotomamonjy; Ugo Tanielian; Clément Calauzènes (CoRR, 2020)

Differentially Private Sliced Wasserstein Distance. - Alain Rakotomamonjy; Liva Ralaivola (ICML, 2021)

Photonic Differential Privacy with Direct Feedback Alignment. - Ruben Ohana; Hamlet Jesse Medina Ruiz; Julien Launay; Alessandro Cappelli; Iacopo Poli; Liva Ralaivola; Alain Rakotomamonjy (NeurIPS, 2021)

Distributional Sliced Embedding Discrepancy for Incomparable Distributions. - Mokhtar Z. Alaya; Gilles Gasso; Maxime Berar; Alain Rakotomamonjy (CoRR, 2021)

Statistical and Topological Properties of Gaussian Smoothed Sliced Probability Divergences. - Alain Rakotomamonjy; Mokhtar Z. Alaya; Maxime Berar; Gilles Gasso (CoRR, 2021)

Unsupervised domain adaptation with non-stochastic missing data. - Matthieu Kirchmeyer; Patrick Gallinari; Alain Rakotomamonjy; Amin Mantrach (Data Min. Knowl. Discov., 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)

Integrating Isolated Examples with Weakly-Supervised Sound Event Detection: A Direct Approach. - Mohammad Abdollahi; Romain Serizel; Alain Rakotomamonjy; Gilles Gasso (DCASE, 2022)

Mapping conditional distributions for domain adaptation under generalized target shift. - Matthieu Kirchmeyer; Alain Rakotomamonjy; Emmanuel de Bézenac; Patrick Gallinari (ICLR, 2022)

Generalizing to New Physical Systems via Context-Informed Dynamics Model. - Matthieu Kirchmeyer; Yuan Yin; Jérémie Donà; Nicolas Baskiotis; Alain Rakotomamonjy; Patrick Gallinari (ICML, 2022)

Benchopt: Reproducible, efficient and collaborative optimization benchmarks. - Thomas Moreau 001; Mathurin Massias; Alexandre Gramfort; Pierre Ablin; Pierre-Antoine Bannier; Benjamin Charlier; Mathieu Dagréou; Tom Dupré la Tour; Ghislain Durif; Cássio F. Dantas; Quentin Klopfenstein; Johan Larsson 002; et al. (NeurIPS, 2022)

Diverse Weight Averaging for Out-of-Distribution Generalization. - Alexandre Ramé; Matthieu Kirchmeyer; Thibaud Rahier; Alain Rakotomamonjy; Patrick Gallinari; Matthieu Cord (NeurIPS, 2022)

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

Theoretical guarantees for bridging metric measure embedding and optimal transport. - Mokhtar Z. Alaya; Maxime Bérar; Gilles Gasso; Alain Rakotomamonjy (Neurocomputing, 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)

Continuous PDE Dynamics Forecasting with Implicit Neural Representations. - Yuan Yin; Matthieu Kirchmeyer; Jean-Yves Franceschi; Alain Rakotomamonjy; Patrick Gallinari (ICLR, 2023)

Sliced-Wasserstein on Symmetric Positive Definite Matrices for M/EEG Signals. - Clément Bonet; Benoît Malézieux; Alain Rakotomamonjy; Lucas Drumetz; Thomas Moreau 001; Matthieu Kowalski; Nicolas Courty (ICML, 2023)

Shedding a PAC-Bayesian Light on Adaptive Sliced-Wasserstein Distances. - Ruben Ohana; Kimia Nadjahi; Alain Rakotomamonjy; Liva Ralaivola (ICML, 2023)

Learning an autoencoder to compress EEG signals via a neural network based approximation of DTW. - Hugo Lerogeron; Romain Picot-Clémente; Laurent Heutte; Alain Rakotomamonjy (INNS DLIA@IJCNN, 2023)

Unifying GANs and Score-Based Diffusion as Generative Particle Models. - Jean-Yves Franceschi; Mike Gartrell; Ludovic Dos Santos; Thibaut Issenhuth; Emmanuel de Bézenac; Mickaël Chen; Alain Rakotomamonjy (NeurIPS, 2023)

Adversarial Sample Detection Through Neural Network Transport Dynamics. - Skander Karkar; Patrick Gallinari; Alain Rakotomamonjy (ECML/PKDD (1), 2023)

Approximating DTW with a convolutional neural network on EEG data. - Hugo Lerogeron; Romain Picot-Clémente; Alain Rakotomamonjy; Laurent Heutte (CoRR, 2023)

Differentially Private Gradient Flow based on the Sliced Wasserstein Distance for Non-Parametric Generative Modeling. - Ilana Sebag; Muni Sreenivas Pydi; Jean-Yves Franceschi; Alain Rakotomamonjy; Mike Gartrell; Jamal Atif; Alexandre Allauzen (CoRR, 2023)

Approximating dynamic time warping with a convolutional neural network on EEG data. - Hugo Lerogeron; Romain Picot-Clémente; Alain Rakotomamonjy; Laurent Heutte (Pattern Recognit. Lett., 2023)

Federated Wasserstein Distance. - Alain Rakotomamonjy; Kimia Nadjahi; Liva Ralaivola (ICLR, 2024)

Open Research Challenges for Private Advertising Systems Under Local Differential Privacy. - Matilde Tullii; Solenne Gaucher; Hugo Richard; Eustache Diemert; Vianney Perchet; Alain Rakotomamonjy; Clément Calauzènes; Maxime Vono (WISE (5), 2024)

Improving Consistency Models with Generator-Induced Coupling. - Thibaut Issenhuth; Ludovic Dos Santos; Jean-Yves Franceschi; Alain Rakotomamonjy (CoRR, 2024)

Gaussian-Smoothed Sliced Probability Divergences. - Mokhtar Z. Alaya; Alain Rakotomamonjy; Maxime Berar; Gilles Gasso (Trans. Mach. Learn. Res., 2024)

Personalised Federated Learning On Heterogeneous Feature Spaces. - Alain Rakotomamonjy; Maxime Vono; Hamlet Jesse Medina Ruiz; Liva Ralaivola (Trans. Mach. Learn. Res., 2024)

Differentially Private Gradient Flow based on the Sliced Wasserstein Distance. - Ilana Sebag; Muni Sreenivas Pydi; Jean-Yves Franceschi; Alain Rakotomamonjy; Mike Gartrell; Jamal Atif; Alexandre Allauzen (Trans. Mach. Learn. Res., 2025)