A. Rakotomamonjy

Alain Rakotomamonjy, Roberto Hirata, Rafael Will M. de Araujo, 2017, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

SVM with feature selection and smooth prediction in images: Application to CAD of prostate cancer

Carole Lartizien, Alain Rakotomamonjy, Rémi Flamary, 2014, 2014 IEEE International Conference on Image Processing (ICIP).

Large Margin Filtering

Alain Rakotomamonjy, Rémi Flamary, Devis Tuia, 2012, IEEE Transactions on Signal Processing.

Decoding Finger Movements from ECoG Signals Using Switching Linear Models

Alain Rakotomamonjy, Rémi Flamary, A. Rakotomamonjy, 2011, Front. Neurosci..

Analysis of SVM regression bounds for variable ranking

Alain Rakotomamonjy, A. Rakotomamonjy, 2007, Neurocomputing.

Photonic Differential Privacy with Direct Feedback Alignment

A. Rakotomamonjy, L. Ralaivola, Julien Launay, 2021, NeurIPS.

Partial Trace Regression and Low-Rank Kraus Decomposition

Liva Ralaivola, Hachem Kadri, Alain Rakotomamonjy, 2020, ICML.

Sliced-Wasserstein on Symmetric Positive Definite Matrices for M/EEG Signals

A. Rakotomamonjy, N. Courty, M. Kowalski, 2023, ICML.

Ieee Transactions on Signal Processing 1 Recovering Sparse Signals with a Certain Family of Non-convex Penalties and Dc Programming

S. Canu, A. Rakotomamonjy, G. Gasso, 2022 .

Variational sequence labeling

A. Rakotomamonjy, R. Flamary, S. Canu, 2009, 2009 IEEE International Workshop on Machine Learning for Signal Processing.

Pedestrian detection using stereo-vision and graph kernels

F. Suard, A. Rakotomamonjy, V. Guigue, 2005, IEEE Proceedings. Intelligent Vehicles Symposium, 2005..

A Pedestrian Detector Using Histograms of Oriented Gradients and a Support Vector Machine Classifier

Alain Rakotomamonjy, Massimo Bertozzi, Alberto Broggi, 2007, 2007 IEEE Intelligent Transportation Systems Conference.

Greedy Methods, Randomization Approaches, and Multiarm Bandit Algorithms for Efficient Sparsity-Constrained Optimization

Liva Ralaivola, Alain Rakotomamonjy, Sokol Koço, 2015, IEEE Transactions on Neural Networks and Learning Systems.

Greedy methods, randomization approaches and multi-arm bandit algorithms for efficient sparsity-constrained optimization

Alain Rakotomamonjy, Liva Ralaivola, Sokol Koço, 2015, IEEE transactions on neural networks and learning systems.

Integrating Isolated Examples with Weakly-Supervised Sound Event Detection: A Direct Approach

A. Rakotomamonjy, R. Serizel, G. Gasso, 2022, Workshop on Detection and Classification of Acoustic Scenes and Events.

Optimal transport Applied to Transfer Learning for P300 Detection

Maureen Clerc, Alain Rakotomamonjy, Nathalie T. H. Gayraud, 2017, GBCIC.

Learning geometric combinations of Gaussian kernels with alternating Quasi-Newton algorithm

Matthieu Cord, Nicolas Thome, David Picard, 2012, ESANN.

Convergent Working Set Algorithm for Lasso with Non-Convex Sparse Regularizers

A. Rakotomamonjy, Rémi Flamary, 2020, AISTATS.

Provably Convergent Working Set Algorithm for Non-Convex Regularized Regression

A. Rakotomamonjy, Rémi Flamary, J. Salmon, 2020, ArXiv.

Surveying and comparing simultaneous sparse approximation (or group-lasso) algorithms

Alain Rakotomamonjy, A. Rakotomamonjy, 2011, Signal Process..

Screening Rules for Lasso with Non-Convex Sparse Regularizers pdf

Alain Rakotomamonjy, Gilles Gasso, Joseph Salmon, 2019, ICML.

Importance sampling strategy for non-convex randomized block-coordinate descent

Alain Rakotomamonjy, Rémi Flamary, Gilles Gasso, 2015, 2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP).

DC Proximal Newton for Nonconvex Optimization Problems

Alain Rakotomamonjy, Rémi Flamary, Gilles Gasso, 2015, IEEE Transactions on Neural Networks and Learning Systems.

Large Scale Sparse Optimization for Object Detection in High Resolution Images

Josiane Zerubia, Alain Rakotomamonjy, Aurélie Boisbunon, 2014 .

Active set strategy for high-dimensional non-convex sparse optimization problems

Alain Rakotomamonjy, Rémi Flamary, Aurelie Boisbunon, 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Applying alternating direction method of multipliers for constrained dictionary learning

Alain Rakotomamonjy, A. Rakotomamonjy, 2013, Neurocomputing.

Shedding a PAC-Bayesian Light on Adaptive Sliced-Wasserstein Distances

A. Rakotomamonjy, L. Ralaivola, Kimia Nadjahi, 2022, ICML.

$\ell_{p}-\ell_{q}$ Penalty for Sparse Linear and Sparse Multiple Kernel Multitask Learning

Stéphane Canu, Alain Rakotomamonjy, Rémi Flamary, 2011, IEEE Transactions on Neural Networks.

Wavelet kernel learning

Florian Yger, Alain Rakotomamonjy, A. Rakotomamonjy, 2011, Pattern Recognit..

Ensemble of SVMs for Improving Brain Computer Interface P300 Speller Performances

Alain Rakotomamonjy, Vincent Guigue, G. Mallet, 2005, ICANN.

Supervised Representation Learning for Audio Scene Classification

Alain Rakotomamonjy, A. Rakotomamonjy, 2017, IEEE/ACM Transactions on Audio, Speech, and Language Processing.

Unifying GANs and Score-Based Diffusion as Generative Particle Models

Ludovic Dos Santos, A. Rakotomamonjy, Jean-Yves Franceschi, 2023, ArXiv.

Randomshot, a fast nonnegative Tucker factorization approach

A. Rakotomamonjy, M. Bérar, A. Traore, 2020 .

Wasserstein discriminant analysis

Nicolas Courty, Alain Rakotomamonjy, Marco Cuturi, 2016, Machine Learning.

Online multimodal dictionary learning through Tucker decomposition

Alain Rakotomamonjy, Abraham Traoré, Maxime Berar, 2019 .

Dissimilarity Measure Machines

Nicolas Courty, Alain Rakotomamonjy, Rémi Flamary, 2018 .

Distance Measure Machines

Nicolas Courty, Maxime Berar, Alain Rakotomamonjy, 2018, 1803.00250.

Automatic Feature Learning for Spatio-Spectral Image Classification With Sparse SVM

Alain Rakotomamonjy, Michele Volpi, Devis Tuia, 2014, IEEE Transactions on Geoscience and Remote Sensing.

Generalized conditional gradient: analysis of convergence and applications pdf

Nicolas Courty, Alain Rakotomamonjy, Rémi Flamary, 2015, ArXiv.

Mixed-Norm Regularization for Brain Decoding

Ronald Phlypo, Marco Congedo, Alain Rakotomamonjy, 2014, Comput. Math. Methods Medicine.

Optimal Transport for Domain Adaptation

A. Rakotomamonjy, N. Courty, Rémi Flamary, 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Multiple Operator-valued Kernel Learning

F. Bach, P. Preux, A. Rakotomamonjy, 2012, Neural Information Processing Systems.

Mining Shock Graphs with Kernels

Alain Rakotomamonjy, Abdelaziz Bensrhair, Frédéric Suard, 2006 .

$\ell_{p}-\ell_{q}$ Penalty for Sparse Linear and Sparse Multiple Kernel Multitask Learning

S. Canu, A. Rakotomamonjy, Rémi Flamary, 2011, IEEE Transactions on Neural Networks.

Functional Regularized Least Squares Classication with Operator-valued Kernels pdf

Philippe Preux, Alain Rakotomamonjy, Asma Rabaoui, 2011, ICML.

A review of classification algorithms for EEG-based brain–computer interfaces: a 10 year update

A. Cichocki, M. Congedo, A. Rakotomamonjy, 2018, Journal of neural engineering.

Optimal Transport for Domain Adaptation

A. Rakotomamonjy, N. Courty, D. Tuia, 2018 .

Chapter 1 Learning constrained task similarities in graph-regularized multi-task learning

A. Rakotomamonjy, Rémi Flamary, G. Gasso, 2022 .

Continuous PDE Dynamics Forecasting with Implicit Neural Representations

P. Gallinari, A. Rakotomamonjy, Jean-Yves Franceschi, 2022, ICLR.

Generalizing to New Physical Systems via Context-Informed Dynamics Model

P. Gallinari, A. Rakotomamonjy, Nicolas Baskiotis, 2022, ICML.

Differentially Private Sliced Wasserstein Distance pdf

Alain Rakotomamonjy, Liva Ralaivola, A. Rakotomamonjy, 2021, ICML.

Heterogeneous Wasserstein Discrepancy for Incomparable Distributions

Alain Rakotomamonjy, Maxime Berar, Gilles Gasso, 2021, 2106.02542.

Distributional Sliced Embedding Discrepancy for Incomparable Distributions pdf

Alain Rakotomamonjy, Maxime Berar, Gilles Gasso, 2021, ArXiv.

Benchopt: Reproducible, efficient and collaborative optimization benchmarks

Tom Dupré la Tour, Binh Duc Nguyen, A. Rakotomamonjy, 2022, Neural Information Processing Systems.

More efficient sparsity-inducing algorithms using inexact gradient

Alain Rakotomamonjy, Liva Ralaivola, Sokol Koço, 2015, 2015 23rd European Signal Processing Conference (EUSIPCO).

Solving non-convex lasso type problems with DC programming

A. Rakotomamonjy, S. Canu, S. Canu, 2008, 2008 IEEE Workshop on Machine Learning for Signal Processing.

ℓp-norm Multiple Kernel Learning with Low-rank Kernels

Alain Rakotomamonjy, Sukalpa Chanda, A. Rakotomamonjy, 2014, Neurocomputing.

Discovering relevant spatial filterbanks for VHR image classification

Alain Rakotomamonjy, Michele Volpi, Devis Tuia, 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).

Unifying GANs and Score-Based Diffusion as Generative Particle Models

Ludovic Dos Santos, A. Rakotomamonjy, Jean-Yves Franceschi, 2023, ArXiv.

BCI Competition III: Dataset II- Ensemble of SVMs for BCI P300 Speller

A. Rakotomamonjy, Vincent Guigue, 2008, IEEE Transactions on Biomedical Engineering.

Statistical Learning for BCIs

Michèle Sebag, Rémi Flamary, Alain Rakotomamonjy, 2016 .

MLSP Competition, 2010: Description of third place method.

Alain Rakotomamonjy, Xilan Tian, Benjamin Labbe, 2010, 2010 IEEE International Workshop on Machine Learning for Signal Processing.

Functional learning through kernel

S. Canu, A. Rakotomamonjy, X. Mary, 2002 .

Greedy Methods, Randomization Approaches, and Multiarm Bandit Algorithms for Efficient Sparsity-Constrained Optimization

A. Rakotomamonjy, L. Ralaivola, Sokol Koço, 2017, IEEE Transactions on Neural Networks and Learning Systems.

Sparse Support Vector Infinite Push

Alain Rakotomamonjy, A. Rakotomamonjy, 2012, ICML.

Screening Sinkhorn Algorithm for Regularized Optimal Transport

Alain Rakotomamonjy, Gilles Gasso, Mokhtar Z. Alaya, 2019, NeurIPS.

Learning spatial filters for multispectral image segmentation

Gustavo Camps-Valls, Alain Rakotomamonjy, Devis Tuia, 2010, 2010 IEEE International Workshop on Machine Learning for Signal Processing.

Scattering features for lung cancer detection in fibered confocal fluorescence microscopy images

A. Rakotomamonjy, C. Petitjean, L. Thiberville, 2014, Artif. Intell. Medicine.

Filter bank Kernel Learning for nonstationary signal classification

Alain Rakotomamonjy, Maxime Sangnier, Jérôme Gauthier, 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

A supervised strategy for deep kernel machine

Florian Yger, Alain Rakotomamonjy, Maxime Berar, 2011, ESANN.

Frames , Reproducing Kernels , Regularization and Learning

S. Canu, A. Rakotomamonjy, 2005 .