Alain Rakotomamonjy

149 papers A* 22A 2B 9C 2Misc 6Journal 86Unranked 22

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Differentially Private Gradient Flow based on the Sliced Wasserstein Distance. Trans. Mach. Learn. Res. Ilana Sebag, Muni Sreenivas Pydi, Jean-Yves Franceschi, Alain Rakotomamonjy, Mike Gartrell, Jamal Atif, Alexandre Allauzen
2025	A*	`conf`	Improving Consistency Models with Generator-Augmented Flows. ICML Thibaut Issenhuth, Sangchul Lee, Ludovic Dos Santos, Jean-Yves Franceschi, Chansoo Kim, Alain Rakotomamonjy
2025	J	`jnl`	On the MIA Vulnerability Gap Between Private GANs and Diffusion Models. CoRR Ilana Sebag, Jean-Yves Franceschi, Alain Rakotomamonjy, Alexandre Allauzen, Jamal Atif
2024	A*	`conf`	Federated Wasserstein Distance. ICLR Alain Rakotomamonjy, Kimia Nadjahi, Liva Ralaivola
2024	J	`jnl`	Gaussian-Smoothed Sliced Probability Divergences. CoRR Mokhtar Z. Alaya, Alain Rakotomamonjy, Maxime Berar, Gilles Gasso
2024	J	`jnl`	Gaussian-Smoothed Sliced Probability Divergences. Trans. Mach. Learn. Res. Mokhtar Z. Alaya, Alain Rakotomamonjy, Maxime Berar, Gilles Gasso
2024	J	`jnl`	Improving Consistency Models with Generator-Induced Coupling. CoRR Thibaut Issenhuth, Ludovic Dos Santos, Jean-Yves Franceschi, Alain Rakotomamonjy
2024	—	`conf`	Open Research Challenges for Private Advertising Systems Under Local Differential Privacy. WISE (5) Matilde Tullii, Solenne Gaucher, Hugo Richard, Eustache Diemert, Vianney Perchet, Alain Rakotomamonjy, Clément Calauzènes, Maxime Vono
2024	J	`jnl`	Personalised Federated Learning On Heterogeneous Feature Spaces. Trans. Mach. Learn. Res. Alain Rakotomamonjy, Maxime Vono, Hamlet Jesse Medina Ruiz, Liva Ralaivola
2023	—	`conf`	Adversarial Sample Detection Through Neural Network Transport Dynamics. ECML/PKDD (1) Skander Karkar, Patrick Gallinari, Alain Rakotomamonjy
2023	J	`jnl`	Adversarial Sample Detection Through Neural Network Transport Dynamics. CoRR Skander Karkar, Patrick Gallinari, Alain Rakotomamonjy
2023	J	`jnl`	Approximating DTW with a convolutional neural network on EEG data. CoRR Hugo Lerogeron, Romain Picot-Clémente, Alain Rakotomamonjy, Laurent Heutte
2023	J	`jnl`	Approximating dynamic time warping with a convolutional neural network on EEG data. Pattern Recognit. Lett. Hugo Lerogeron, Romain Picot-Clémente, Alain Rakotomamonjy, Laurent Heutte
2023	A*	`conf`	Continuous PDE Dynamics Forecasting with Implicit Neural Representations. ICLR Yuan Yin, Matthieu Kirchmeyer, Jean-Yves Franceschi, Alain Rakotomamonjy, Patrick Gallinari
2023	J	`jnl`	Differentially Private Gradient Flow based on the Sliced Wasserstein Distance for Non-Parametric Generative Modeling. CoRR Ilana Sebag, Muni Sreenivas Pydi, Jean-Yves Franceschi, Alain Rakotomamonjy, Mike Gartrell, Jamal Atif, Alexandre Allauzen
2023	J	`jnl`	Federated Wasserstein Distance. CoRR Alain Rakotomamonjy, Kimia Nadjahi, Liva Ralaivola
2023	—	`conf`	Learning an autoencoder to compress EEG signals via a neural network based approximation of DTW. INNS DLIA@IJCNN Hugo Lerogeron, Romain Picot-Clémente, Laurent Heutte, Alain Rakotomamonjy
2023	J	`jnl`	Personalised Federated Learning On Heterogeneous Feature Spaces. CoRR Alain Rakotomamonjy, Maxime Vono, Hamlet Jesse Medina Ruiz, Liva Ralaivola
2023	A*	`conf`	Shedding a PAC-Bayesian Light on Adaptive Sliced-Wasserstein Distances. ICML Ruben Ohana, Kimia Nadjahi, Alain Rakotomamonjy, Liva Ralaivola
2023	A*	`conf`	Sliced-Wasserstein on Symmetric Positive Definite Matrices for M/EEG Signals. ICML Clément Bonet, Benoît Malézieux, Alain Rakotomamonjy, Lucas Drumetz, Thomas Moreau, Matthieu Kowalski, Nicolas Courty
2023	J	`jnl`	Sliced-Wasserstein on Symmetric Positive Definite Matrices for M/EEG Signals. CoRR Clément Bonet, Benoît Malézieux, Alain Rakotomamonjy, Lucas Drumetz, Thomas Moreau, Matthieu Kowalski, Nicolas Courty
2023	A*	`conf`	Unifying GANs and Score-Based Diffusion as Generative Particle Models. NeurIPS Jean-Yves Franceschi, Mike Gartrell, Ludovic Dos Santos, Thibaut Issenhuth, Emmanuel de Bézenac, Mickaël Chen, Alain Rakotomamonjy
2023	J	`jnl`	Unifying GANs and Score-Based Diffusion as Generative Particle Models. CoRR Jean-Yves Franceschi, Mike Gartrell, Ludovic Dos Santos, Thibaut Issenhuth, Emmanuel de Bézenac, Mickaël Chen, Alain Rakotomamonjy
2022	A*	`conf`	Benchopt: Reproducible, efficient and collaborative optimization benchmarks. NeurIPS Thomas Moreau, 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, En Lai, Tanguy Lefort, Benoît Malézieux, Badr Moufad, Binh T. Nguyen, Alain Rakotomamonjy, Zaccharie Ramzi, Joseph Salmon, Samuel Vaiter
2022	J	`jnl`	Benchopt: Reproducible, efficient and collaborative optimization benchmarks. CoRR Thomas Moreau, 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, En Lai, Tanguy Lefort, Benoît Malézieux, Badr Moufad, Binh T. Nguyen, Alain Rakotomamonjy, Zaccharie Ramzi, Joseph Salmon, Samuel Vaiter
2022	J	`jnl`	Continuous PDE Dynamics Forecasting with Implicit Neural Representations. CoRR Yuan Yin, Matthieu Kirchmeyer, Jean-Yves Franceschi, Alain Rakotomamonjy, Patrick Gallinari
2022	A	`conf`	Convergent Working Set Algorithm for Lasso with Non-Convex Sparse Regularizers. AISTATS Alain Rakotomamonjy, Rémi Flamary, Joseph Salmon, Gilles Gasso
2022	A*	`conf`	Diverse Weight Averaging for Out-of-Distribution Generalization. NeurIPS Alexandre Ramé, Matthieu Kirchmeyer, Thibaud Rahier, Alain Rakotomamonjy, Patrick Gallinari, Matthieu Cord
2022	J	`jnl`	Diverse Weight Averaging for Out-of-Distribution Generalization. CoRR Alexandre Ramé, Matthieu Kirchmeyer, Thibaud Rahier, Alain Rakotomamonjy, Patrick Gallinari, Matthieu Cord
2022	A*	`conf`	Generalizing to New Physical Systems via Context-Informed Dynamics Model. ICML Matthieu Kirchmeyer, Yuan Yin, Jérémie Donà, Nicolas Baskiotis, Alain Rakotomamonjy, Patrick Gallinari
2022	J	`jnl`	Generalizing to New Physical Systems via Context-Informed Dynamics Model. CoRR Matthieu Kirchmeyer, Yuan Yin, Jérémie Donà, Nicolas Baskiotis, Alain Rakotomamonjy, Patrick Gallinari
2022	—	`conf`	Integrating Isolated Examples with Weakly-Supervised Sound Event Detection: A Direct Approach. DCASE Mohammad Abdollahi, Romain Serizel, Alain Rakotomamonjy, Gilles Gasso
2022	A*	`conf`	Mapping conditional distributions for domain adaptation under generalized target shift. ICLR Matthieu Kirchmeyer, Alain Rakotomamonjy, Emmanuel de Bézenac, Patrick Gallinari
2022	A	`conf`	Multi-source domain adaptation via weighted joint distributions optimal transport. UAI Rosanna Turrisi, Rémi Flamary, Alain Rakotomamonjy, Massimiliano Pontil
2022	J	`jnl`	Optimal transport for conditional domain matching and label shift. Mach. Learn. Alain Rakotomamonjy, Rémi Flamary, Gilles Gasso, M. El Alaya, Maxime Berar, Nicolas Courty
2022	J	`jnl`	Shedding a PAC-Bayesian Light on Adaptive Sliced-Wasserstein Distances. CoRR Ruben Ohana, Kimia Nadjahi, Alain Rakotomamonjy, Liva Ralaivola
2022	J	`jnl`	Theoretical guarantees for bridging metric measure embedding and optimal transport. Neurocomputing Mokhtar Z. Alaya, Maxime Bérar, Gilles Gasso, Alain Rakotomamonjy
2021	A*	`conf`	Differentially Private Sliced Wasserstein Distance. ICML Alain Rakotomamonjy, Liva Ralaivola
2021	J	`jnl`	Differentially Private Sliced Wasserstein Distance. CoRR Alain Rakotomamonjy, Liva Ralaivola
2021	J	`jnl`	Distributional Sliced Embedding Discrepancy for Incomparable Distributions. CoRR Mokhtar Z. Alaya, Gilles Gasso, Maxime Berar, Alain Rakotomamonjy
2021	J	`jnl`	Mapping conditional distributions for domain adaptation under generalized target shift. CoRR Matthieu Kirchmeyer, Alain Rakotomamonjy, Emmanuel de Bézenac, Patrick Gallinari
2021	J	`jnl`	POT: Python Optimal Transport. J. Mach. Learn. Res. 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
2021	A*	`conf`	Photonic Differential Privacy with Direct Feedback Alignment. NeurIPS Ruben Ohana, Hamlet Jesse Medina Ruiz, Julien Launay, Alessandro Cappelli, Iacopo Poli, Liva Ralaivola, Alain Rakotomamonjy
2021	J	`jnl`	Photonic Differential Privacy with Direct Feedback Alignment. CoRR Ruben Ohana, Hamlet Jesse Medina Ruiz, Julien Launay, Alessandro Cappelli, Iacopo Poli, Liva Ralaivola, Alain Rakotomamonjy
2021	J	`jnl`	Statistical and Topological Properties of Gaussian Smoothed Sliced Probability Divergences. CoRR Alain Rakotomamonjy, Mokhtar Z. Alaya, Maxime Berar, Gilles Gasso
2021	J	`jnl`	Unsupervised domain adaptation with non-stochastic missing data. CoRR Matthieu Kirchmeyer, Patrick Gallinari, Alain Rakotomamonjy, Amin Mantrach
2021	J	`jnl`	Unsupervised domain adaptation with non-stochastic missing data. Data Min. Knowl. Discov. Matthieu Kirchmeyer, Patrick Gallinari, Alain Rakotomamonjy, Amin Mantrach
2020	J	`jnl`	Match and Reweight Strategy for Generalized Target Shift. CoRR Alain Rakotomamonjy, Rémi Flamary, Gilles Gasso, Mokhtar Z. Alaya, Maxime Berar, Nicolas Courty
2020	J	`jnl`	Multi-source Domain Adaptation via Weighted Joint Distributions Optimal Transport. CoRR Rosanna Turrisi, Rémi Flamary, Alain Rakotomamonjy, Massimiliano Pontil
2020	J	`jnl`	Non-Aligned Distribution Distance using Metric Measure Embedding and Optimal Transport. CoRR Mokhtar Z. Alaya, Maxime Bérar, Gilles Gasso, Alain Rakotomamonjy
2020	A*	`conf`	Partial Trace Regression and Low-Rank Kraus Decomposition. ICML Hachem Kadri, Stéphane Ayache, Riikka Huusari, Alain Rakotomamonjy, Liva Ralaivola
2020	J	`jnl`	Partial Trace Regression and Low-Rank Kraus Decomposition. CoRR Hachem Kadri, Stéphane Ayache, Riikka Huusari, Alain Rakotomamonjy, Liva Ralaivola
2020	J	`jnl`	Provably Convergent Working Set Algorithm for Non-Convex Regularized Regression. CoRR Alain Rakotomamonjy, Rémi Flamary, Gilles Gasso, Joseph Salmon
2020	J	`jnl`	Wasserstein Learning of Determinantal Point Processes. CoRR Lucas Anquetil, Mike Gartrell, Alain Rakotomamonjy, Ugo Tanielian, Clément Calauzènes
2019	J	`jnl`	Online multimodal dictionary learning. Neurocomputing Abraham Traoré, Maxime Berar, Alain Rakotomamonjy
2019	J	`jnl`	Screening Rules for Lasso with Non-Convex Sparse Regularizers. CoRR Alain Rakotomamonjy, Gilles Gasso, Joseph Salmon
2019	A*	`conf`	Screening Sinkhorn Algorithm for Regularized Optimal Transport. NeurIPS Mokhtar Z. Alaya, Maxime Berar, Gilles Gasso, Alain Rakotomamonjy
2019	J	`jnl`	Screening Sinkhorn Algorithm for Regularized Optimal Transport. CoRR Mokhtar Z. Alaya, Maxime Bérar, Gilles Gasso, Alain Rakotomamonjy
2019	A*	`conf`	Screening rules for Lasso with non-convex Sparse Regularizers. ICML Alain Rakotomamonjy, Gilles Gasso, Joseph Salmon
2019	A*	`conf`	Singleshot : a scalable Tucker tensor decomposition. NeurIPS Abraham Traoré, Maxime Berar, Alain Rakotomamonjy
2018	Misc	`conf`	Concave Losses for Robust Dictionary Learning. ICASSP Rafael Will M. de Araujo, Roberto Hirata, Alain Rakotomamonjy
2018	B	`conf`	Non-Negative Tensor Dictionary Learning. ESANN Abraham Traoré, Maxime Berar, Alain Rakotomamonjy
2018	J	`jnl`	Wasserstein Distance Measure Machines. CoRR Alain Rakotomamonjy, Abraham Traoré, Maxime Berar, Rémi Flamary, Nicolas Courty
2018	J	`jnl`	Wasserstein discriminant analysis. Mach. Learn. Rémi Flamary, Marco Cuturi, Nicolas Courty, Alain Rakotomamonjy
2017	J	`jnl`	Concave losses for robust dictionary learning. CoRR Rafael Will M. de Araujo, Roberto Hirata, Alain Rakotomamonjy
2017	J	`jnl`	Editorial: A Successful Year and Looking Forward to 2017 and Beyond. IEEE Trans. Neural Networks Learn. Syst. Haibo He, Robert Haas, Jun Fu, Barbara Hammer, Daniel W. C. Ho, Fakhri Karray, Dhireesha Kudithipudi, José Antonio Lozano, Teresa Bernarda Ludermir, Jacek Mandziuk, Stefano Melacci, Antonio Paiva, Hong Qiao, Alain Rakotomamonjy, Shiliang Sun, Johan A. K. Suykens, Meng Wang
2017	J	`jnl`	Greedy Methods, Randomization Approaches, and Multiarm Bandit Algorithms for Efficient Sparsity-Constrained Optimization. IEEE Trans. Neural Networks Learn. Syst. Alain Rakotomamonjy, Sokol Koço, Liva Ralaivola
2017	J	`jnl`	Joint Distribution Optimal Transportation for Domain Adaptation. CoRR Nicolas Courty, Rémi Flamary, Amaury Habrard, Alain Rakotomamonjy
2017	—	`conf`	Joint distribution optimal transportation for domain adaptation. NIPS Nicolas Courty, Rémi Flamary, Amaury Habrard, Alain Rakotomamonjy
2017	J	`jnl`	Optimal Transport for Domain Adaptation. IEEE Trans. Pattern Anal. Mach. Intell. Nicolas Courty, Rémi Flamary, Devis Tuia, Alain Rakotomamonjy
2017	—	`conf`	Optimal transport Applied to Transfer Learning for P300 Detection. GBCIC Nathalie T. H. Gayraud, Alain Rakotomamonjy, Maureen Clerc
2017	J	`jnl`	Supervised Representation Learning for Audio Scene Classification. IEEE ACM Trans. Audio Speech Lang. Process. Alain Rakotomamonjy
2016	J	`jnl`	DC Proximal Newton for Nonconvex Optimization Problems. IEEE Trans. Neural Networks Learn. Syst. Alain Rakotomamonjy, Rémi Flamary, Gilles Gasso
2016	A*	`conf`	Early and Reliable Event Detection Using Proximity Space Representation. ICML Maxime Sangnier, Jérôme Gauthier, Alain Rakotomamonjy
2016	J	`jnl`	Importance sampling strategy for non-convex randomized block-coordinate descent. CoRR Rémi Flamary, Alain Rakotomamonjy, Gilles Gasso
2016	J	`jnl`	Operator-valued Kernels for Learning from Functional Response Data. J. Mach. Learn. Res. Hachem Kadri, Emmanuel Duflos, Philippe Preux, Stéphane Canu, Alain Rakotomamonjy, Julien Audiffren
2016	J	`jnl`	Wasserstein Discriminant Analysis. CoRR Rémi Flamary, Marco Cuturi, Nicolas Courty, Alain Rakotomamonjy
2015	J	`jnl`	DC Proximal Newton for Non-Convex Optimization Problems. CoRR Alain Rakotomamonjy, Rémi Flamary, Gilles Gasso
2015	—	`conf`	Early frame-based detection of acoustic scenes. WASPAA Maxime Sangnier, Jérôme Gauthier, Alain Rakotomamonjy
2015	J	`jnl`	Filter bank learning for signal classification. Signal Process. Maxime Sangnier, Jérôme Gauthier, Alain Rakotomamonjy
2015	J	`jnl`	Generalized conditional gradient: analysis of convergence and applications. CoRR Alain Rakotomamonjy, Rémi Flamary, Nicolas Courty
2015	J	`jnl`	Greedy methods, randomization approaches and multi-arm bandit algorithms for efficient sparsity-constrained optimization. CoRR Alain Rakotomamonjy, Sokol Koço, Liva Ralaivola
2015	J	`jnl`	Histogram of Gradients of Time-Frequency Representations for Audio Scene Classification. IEEE ACM Trans. Audio Speech Lang. Process. Alain Rakotomamonjy, Gilles Gasso
2015	J	`jnl`	Histogram of gradients of Time-Frequency Representations for Audio scene detection. CoRR Alain Rakotomamonjy, Gilles Gasso
2015	—	`conf`	Importance sampling strategy for non-convex randomized block-coordinate descent. CAMSAP Rémi Flamary, Alain Rakotomamonjy, Gilles Gasso
2015	—	`conf`	More efficient sparsity-inducing algorithms using inexact gradient. EUSIPCO Alain Rakotomamonjy, Sokol Koço, Liva Ralaivola
2015	—	`conf`	Multitemporal classification without new labels: A solution with optimal transport. MultiTemp Devis Tuia, Rémi Flamary, Alain Rakotomamonjy, Nicolas Courty
2015	J	`jnl`	Operator-valued Kernels for Learning from Functional Response Data. CoRR Hachem Kadri, Emmanuel Duflos, Philippe Preux, Stéphane Canu, Alain Rakotomamonjy, Julien Audiffren
2015	J	`jnl`	Optimal Transport for Domain Adaptation. CoRR Nicolas Courty, Rémi Flamary, Devis Tuia, Alain Rakotomamonjy
2014	Misc	`conf`	Active set strategy for high-dimensional non-convex sparse optimization problems. ICASSP Aurelie Boisbunon, Rémi Flamary, Alain Rakotomamonjy
2014	J	`jnl`	Automatic Feature Learning for Spatio-Spectral Image Classification With Sparse SVM. IEEE Trans. Geosci. Remote. Sens. Devis Tuia, Michele Volpi, Mauro Dalla Mura, Alain Rakotomamonjy, Rémi Flamary
2014	—	`conf`	Kernel learning as minimization of the single validation estimate. MLSP Maxime Sangnier, Jérôme Gauthier, Alain Rakotomamonjy
2014	J	`jnl`	Mixed-Norm Regularization for Brain Decoding. Comput. Math. Methods Medicine Rémi Flamary, Nisrine Jrad, Ronald Phlypo, Marco Congedo, Alain Rakotomamonjy
2014	J	`jnl`	Mixed-norm Regularization for Brain Decoding. CoRR Rémi Flamary, Nisrine Jrad, Ronald Phlypo, Marco Congedo, Alain Rakotomamonjy
2014	B	`conf`	SVM with feature selection and smooth prediction in images: Application to CAD of prostate cancer. ICIP Emilie Niaf, Rémi Flamary, Alain Rakotomamonjy, Olivier Rouvière, Carole Lartizien
2014	J	`jnl`	Scattering features for lung cancer detection in fibered confocal fluorescence microscopy images. Artif. Intell. Medicine Alain Rakotomamonjy, Caroline Petitjean, Mathieu Salaün, Luc Thiberville
2014	J	`jnl`	ℓ Neurocomputing Alain Rakotomamonjy, Sukalpa Chanda
2013	J	`jnl`	Applying alternating direction method of multipliers for constrained dictionary learning. Neurocomputing Alain Rakotomamonjy
2013	C	`conf`	Create the relevant spatial filterbank in the hyperspectral jungle. IGARSS Devis Tuia, Michele Volpi, Mauro Dalla Mura, Alain Rakotomamonjy, Rémi Flamary
2013	J	`jnl`	Direct Optimization of the Dictionary Learning Problem. IEEE Trans. Signal Process. Alain Rakotomamonjy
2013	Misc	`conf`	Filter bank Kernel Learning for nonstationary signal classification. ICASSP Maxime Sangnier, Jérôme Gauthier, Alain Rakotomamonjy
2013	J	`jnl`	Functional Regularized Least Squares Classi cation with Operator-valued Kernels CoRR Hachem Kadri, Asma Rabaoui, Philippe Preux, Emmanuel Duflos, Alain Rakotomamonjy
2013	J	`jnl`	Learning with infinitely many features. Mach. Learn. Alain Rakotomamonjy, Rémi Flamary, Florian Yger
2012	A*	`conf`	Adaptive Canonical Correlation Analysis Based On Matrix Manifolds. ICML Florian Yger, Maxime Berar, Gilles Gasso, Alain Rakotomamonjy
2012	B	`conf`	Discovering relevant spatial filterbanks for VHR image classification. ICPR Devis Tuia, Mauro Dalla Mura, Michele Volpi, Rémi Flamary, Alain Rakotomamonjy
2012	J	`jnl`	Large Margin Filtering. IEEE Trans. Signal Process. Rémi Flamary, Devis Tuia, Benjamin Labbé, Gustavo Camps-Valls, Alain Rakotomamonjy
2012	B	`conf`	Learning geometric combinations of Gaussian kernels with alternating Quasi-Newton algorithm. ESANN David Picard, Nicolas Thome, Matthieu Cord, Alain Rakotomamonjy
2012	J	`jnl`	Multiple Operator-valued Kernel Learning CoRR Hachem Kadri, Alain Rakotomamonjy, Francis R. Bach, Philippe Preux
2012	—	`conf`	Multiple Operator-valued Kernel Learning. NIPS Hachem Kadri, Alain Rakotomamonjy, Francis R. Bach, Philippe Preux
2012	Misc	`conf`	Oblique principal subspace tracking on manifold. ICASSP Florian Yger, Maxime Berar, Gilles Gasso, Alain Rakotomamonjy
2012	A*	`conf`	Sparse Support Vector Infinite Push. ICML Alain Rakotomamonjy
2011	B	`conf`	A supervised strategy for deep kernel machine. ESANN Florian Yger, Maxime Berar, Gilles Gasso, Alain Rakotomamonjy
2011	J	`jnl`	Apprentissage de dictionnaires d'ondelettes vaste marge pour la classification de signaux et de textures. Rev. d'Intelligence Artif. Florian Yger, Alain Rakotomamonjy
2011	J	`jnl`	Decoding finger movements from ECoG signals using switching linear models CoRR Rémi Flamary, Alain Rakotomamonjy
2011	A*	`conf`	Functional Regularized Least Squares Classication with Operator-valued Kernels. ICML Hachem Kadri, Asma Rabaoui, Philippe Preux, Emmanuel Duflos, Alain Rakotomamonjy
2011	J	`jnl`	Large margin filtering for signal sequence labeling CoRR Rémi Flamary, Benjamin Labbé, Alain Rakotomamonjy
2011	B	`conf`	Selecting from an infinite set of features in SVM. ESANN Rémi Flamary, Florian Yger, Alain Rakotomamonjy
2011	J	`jnl`	Surveying and comparing simultaneous sparse approximation (or group-lasso) algorithms. Signal Process. Alain Rakotomamonjy
2011	J	`jnl`	Wavelet kernel learning. Pattern Recognit. Florian Yger, Alain Rakotomamonjy
2011	J	`jnl`	ell IEEE Trans. Neural Networks Alain Rakotomamonjy, Rémi Flamary, Gilles Gasso, Stéphane Canu
2010	J	`jnl`	Composite kernel learning. Mach. Learn. Marie Szafranski, Yves Grandvalet, Alain Rakotomamonjy
2010	J	`jnl`	Filtrage vaste marge pour l'étiquetage séquentiel à noyaux de signaux CoRR Rémi Flamary, Benjamin Labbé, Alain Rakotomamonjy
2010	Misc	`conf`	Large margin filtering for Signal Sequence Labeling. ICASSP Rémi Flamary, Benjamin Labbé, Alain Rakotomamonjy
2010	Misc	`conf`	Large marginwavelet-based dictionary for signal classification. ICASSP Florian Yger, Alain Rakotomamonjy
2009	J	`jnl`	Recovering sparse signals with a certain family of nonconvex penalties and DC programming. IEEE Trans. Signal Process. Gilles Gasso, Alain Rakotomamonjy, Stéphane Canu
2008	J	`jnl`	BCI Competition III: Dataset II- Ensemble of SVMs for BCI P300 Speller. IEEE Trans. Biomed. Eng. Alain Rakotomamonjy, Vincent Guigue
2008	A*	`conf`	Composite kernel learning. ICML Marie Szafranski, Yves Grandvalet, Alain Rakotomamonjy
2008	—	`conf`	Support Vector Machines with a Reject Option. NIPS Yves Grandvalet, Alain Rakotomamonjy, Joseph Keshet, Stéphane Canu
2007	—	`conf`	A Pedestrian Detector Using Histograms of Oriented Gradients and a Support Vector Machine Classifier. ITSC Massimo Bertozzi, Alberto Broggi, Michael S. Del Rose, Mirko Felisa, Alain Rakotomamonjy, Frédéric Suard
2007	J	`jnl`	Analysis of SVM regression bounds for variable ranking. Neurocomputing Alain Rakotomamonjy
2007	B	`conf`	Kernel on Bag of Paths For Measuring Similarity of Shapes. ESANN Frédéric Suard, Alain Rakotomamonjy, Abdelaziz Bensrhair
2007	A*	`conf`	More efficiency in multiple kernel learning. ICML Alain Rakotomamonjy, Francis R. Bach, Stéphane Canu, Yves Grandvalet
2007	B	`conf`	One-class SVM regularization path and comparison with alpha seeding. ESANN Alain Rakotomamonjy, Manuel Davy
2006	J	`jnl`	Kernel Basis Pursuit. Rev. d'Intelligence Artif. Vincent Guigue, Alain Rakotomamonjy, Stéphane Canu
2006	—	`conf`	Object Categorization Using Kernels Combining Graphs and Histograms of Gradients. ICIAR (2) Frédéric Suard, Alain Rakotomamonjy, Abdelaziz Bensrhair
2006	J	`jnl`	Perception d'états affectifs et apprentissage. Rev. d'Intelligence Artif. Gaëlle Loosli, Sans-Goog Lee, Alain Rakotomamonjy
2006	J	`jnl`	Translation-invariant classification of non-stationary signals. Neurocomputing Vincent Guigue, Alain Rakotomamonjy, Stéphane Canu
2005	—	`conf`	Ensemble of SVMs for Improving Brain Computer Interface P300 Speller Performances. ICANN (1) Alain Rakotomamonjy, Vincent Guigue, Grégory Mallet, Victor Alvarado
2005	—	`conf`	Evaluation of the quality of ultrasound image compression by fusion of criteria with a support vector machine. EUSIPCO Cécile Delgorge, Christophe Rosenberger, Alain Rakotomamonjy, Gérard Poisson, Pierre Vieyres
2005	J	`jnl`	Frames, Reproducing Kernels, Regularization and Learning. J. Mach. Learn. Res. Alain Rakotomamonjy, Stéphane Canu
2005	—	`conf`	Kernel Basis Pursuit. CAP Vincent Guigue, Alain Rakotomamonjy, Stéphane Canu
2005	—	`conf`	Kernel Basis Pursuit. ECML Vincent Guigue, Alain Rakotomamonjy, Stéphane Canu
2005	—	`conf`	Segmentation Evaluation Using a Support Vector Machine. ICAPR (1) Sébastien Chabrier, Christophe Rosenberger, Hélène Laurent, Alain Rakotomamonjy
2005	B	`conf`	Translation invariant classification of non-stationary signals. ESANN Vincent Guigue, Alain Rakotomamonjy, Stéphane Canu
2004	—	`conf`	Generic target recognition. EUSIPCO Christophe Rosenberger, Alain Rakotomamonjy, Bruno Emile
2004	—	`conf`	Optimizing Area Under Roc Curve with SVMs. ROCAI Alain Rakotomamonjy
2003	J	`jnl`	Variable Selection Using SVM-based Criteria. J. Mach. Learn. Res. Alain Rakotomamonjy
2002	J	`jnl`	Comparaison de stratégies de discrimination de masses de véhicules automobiles. Rev. d'Intelligence Artif. Alain Rakotomamonjy, Rodolphe Le Riche, David Gualandris, Stéphane Canu
2002	C	`conf`	Frame Kernels for Learning. ICANN Alain Rakotomamonjy, Stéphane Canu