Rakotomamonjy, Alain

43 publications

TMLR 2025 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

ICML 2025 Improving Consistency Models with Generator-Augmented Flows Thibaut Issenhuth, Sangchul Lee, Ludovic Dos Santos, Jean-Yves Franceschi, Chansoo Kim, Alain Rakotomamonjy

ICLR 2024 Federated Wasserstein Distance Alain Rakotomamonjy, Kimia Nadjahi, Liva Ralaivola

TMLR 2024 Gaussian-Smoothed Sliced Probability Divergences Mokhtar Z. Alaya, Alain Rakotomamonjy, Maxime Berar, Gilles Gasso

ICMLW 2024 Improving Consistency Models with Generator-Induced Coupling Thibaut Issenhuth, Ludovic Dos Santos, Jean-Yves Franceschi, Alain Rakotomamonjy

TMLR 2024 Personalised Federated Learning on Heterogeneous Feature Spaces Alain Rakotomamonjy, Maxime Vono, Hamlet Jesse Medina Ruiz, Liva Ralaivola

ECML-PKDD 2023 Adversarial Sample Detection Through Neural Network Transport Dynamics Skander Karkar, Patrick Gallinari, Alain Rakotomamonjy

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

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

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

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

AISTATS 2022 Convergent Working Set Algorithm for Lasso with Non-Convex Sparse Regularizers Alain Rakotomamonjy, Rémi Flamary, Joseph Salmon, Gilles Gasso

NeurIPS 2022 Benchopt: Reproducible, Efficient and Collaborative Optimization Benchmarks Thomas Moreau, Mathurin Massias, Alexandre Gramfort, Pierre Ablin, Pierre-Antoine Bannier, Benjamin Charlier, Mathieu Dagréou, Tom Dupre la Tour, Ghislain Durif, Cassio 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

NeurIPSW 2022 Continuous PDE Dynamics Forecasting with Implicit Neural Representations Yuan Yin, Matthieu Kirchmeyer, Jean-Yves Franceschi, Alain Rakotomamonjy, Patrick Gallinari

NeurIPS 2022 Diverse Weight Averaging for Out-of-Distribution Generalization Alexandre Rame, Matthieu Kirchmeyer, Thibaud Rahier, Alain Rakotomamonjy, Patrick Gallinari, Matthieu Cord

ICML 2022 Generalizing to New Physical Systems via Context-Informed Dynamics Model Matthieu Kirchmeyer, Yuan Yin, Jeremie Dona, Nicolas Baskiotis, Alain Rakotomamonjy, Patrick Gallinari

ICLR 2022 Mapping Conditional Distributions for Domain Adaptation Under Generalized Target Shift Matthieu Kirchmeyer, Alain Rakotomamonjy, Emmanuel de Bezenac, Patrick Gallinari

UAI 2022 Multi-Source Domain Adaptation via Weighted Joint Distributions Optimal Transport Rosanna Turrisi, Rémi Flamary, Alain Rakotomamonjy, Massimiliano Pontil

MLJ 2022 Optimal Transport for Conditional Domain Matching and Label Shift Alain Rakotomamonjy, Rémi Flamary, Gilles Gasso, M. El Alaya, Maxime Berar, Nicolas Courty

ICML 2021 Differentially Private Sliced Wasserstein Distance Alain Rakotomamonjy, Ralaivola Liva

MLOSS 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, Hicham Janati, Alain Rakotomamonjy, Ievgen Redko, Antoine Rolet, Antony Schutz, Vivien Seguy, Danica J. Sutherland, Romain Tavenard, Alexander Tong, Titouan Vayer

NeurIPS 2021 Photonic Differential Privacy with Direct Feedback Alignment Ruben Ohana, Hamlet Medina, Julien Launay, Alessandro Cappelli, Iacopo Poli, Liva Ralaivola, Alain Rakotomamonjy

ICML 2020 Partial Trace Regression and Low-Rank Kraus Decomposition Hachem Kadri, Stephane Ayache, Riikka Huusari, Alain Rakotomamonjy, Ralaivola Liva

NeurIPSW 2020 Wasserstein Learning of Determinantal Point Processes Lucas Anquetil, Mike Gartrell, Alain Rakotomamonjy, Ugo Tanielian, Clément Calauzènes

ICML 2019 Screening Rules for Lasso with Non-Convex Sparse Regularizers Alain Rakotomamonjy, Gilles Gasso, Joseph Salmon

NeurIPS 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 Traore, Maxime Berar, Alain Rakotomamonjy

MLJ 2018 Wasserstein Discriminant Analysis Rémi Flamary, Marco Cuturi, Nicolas Courty, Alain Rakotomamonjy

NeurIPS 2017 Joint Distribution Optimal Transportation for Domain Adaptation Nicolas Courty, Rémi Flamary, Amaury Habrard, Alain Rakotomamonjy

ICML 2016 Early and Reliable Event Detection Using Proximity Space Representation Maxime Sangnier, Jerome Gauthier, Alain Rakotomamonjy

JMLR 2016 Operator-Valued Kernels for Learning from Functional Response Data Hachem Kadri, Emmanuel Duflos, Philippe Preux, Stéphane Canu, Alain Rakotomamonjy, Julien Audiffren

MLJ 2013 Learning with Infinitely Many Features Alain Rakotomamonjy, Rémi Flamary, Florian Yger

ICML 2012 Adaptive Canonical Correlation Analysis Based on Matrix Manifolds Florian Yger, Maxime Berar, Gilles Gasso, Alain Rakotomamonjy

NeurIPS 2012 Multiple Operator-Valued Kernel Learning Hachem Kadri, Alain Rakotomamonjy, Philippe Preux, Francis R. Bach

ICML 2012 Sparse Support Vector Infinite Push Alain Rakotomamonjy

ICML 2011 Functional Regularized Least Squares Classication with Operator-Valued Kernels Hachem Kadri, Asma Rabaoui, Philippe Preux, Emmanuel Duflos, Alain Rakotomamonjy

MLJ 2010 Composite Kernel Learning Marie Szafranski, Yves Grandvalet, Alain Rakotomamonjy

ICML 2008 Composite Kernel Learning Marie Szafranski, Yves Grandvalet, Alain Rakotomamonjy

JMLR 2008 SimpleMKL Alain Rakotomamonjy, Francis R. Bach, Stéphane Canu, Yves Grandvalet

NeurIPS 2008 Support Vector Machines with a Reject Option Yves Grandvalet, Alain Rakotomamonjy, Joseph Keshet, Stéphane Canu

ICML 2007 More Efficiency in Multiple Kernel Learning Alain Rakotomamonjy, Francis R. Bach, Stéphane Canu, Yves Grandvalet

JMLR 2005 Frames, Reproducing Kernels, Regularization and Learning Alain Rakotomamonjy, Stéphane Canu

ECML-PKDD 2005 Kernel Basis Pursuit Vincent Guigue, Alain Rakotomamonjy, Stéphane Canu