activity
20102025
most citedSparse Support Vector Infinite Push

14 citations · 24 across the 11 of their papers we have counts for

collaborators

11 papers

cs.LG2025

On the MIA Vulnerability Gap Between Private GANs and Diffusion Models

Ilana Sebag, Jean-Yves Franceschi, Alain Rakotomamonjy +2

Generative Adversarial Networks (GANs) and diffusion models have emerged as leading approaches for high-quality image synthesis. While both can be trained under differential privac…

cs.LG2024

Gaussian-Smoothed Sliced Probability Divergences

Mokhtar Z. Alaya, Alain Rakotomamonjy, Maxime Berar +1

Gaussian smoothed sliced Wasserstein distance has been recently introduced for comparing probability distributions, while preserving privacy on the data. It has been shown that it…

cs.LG20232 cited

Federated Wasserstein Distance

Alain Rakotomamonjy, Kimia Nadjahi, Liva Ralaivola

We introduce a principled way of computing the Wasserstein distance between two distributions in a federated manner. Namely, we show how to estimate the Wasserstein distance betwee…

cs.LG2023

Adversarial Sample Detection Through Neural Network Transport Dynamics

Skander Karkar, Patrick Gallinari, Alain Rakotomamonjy

We propose a detector of adversarial samples that is based on the view of neural networks as discrete dynamic systems. The detector tells clean inputs from abnormal ones by compari…

cs.LG20231 cited

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

Clément Bonet, Benoît Malézieux, Alain Rakotomamonjy +4

When dealing with electro or magnetoencephalography records, many supervised prediction tasks are solved by working with covariance matrices to summarize the signals. Learning with…

cs.LG2023

Approximating DTW with a convolutional neural network on EEG data

Hugo Lerogeron, Romain Picot-Clemente, Alain Rakotomamonjy +1

Dynamic Time Wrapping (DTW) is a widely used algorithm for measuring similarities between two time series. It is especially valuable in a wide variety of applications, such as clus…