3 papers
cs.LG2026
Disparate Impact in Synthetic Data Generation
Paul Andrey, Michaël Perrot, Batiste Le Bars +1
We revisit the fairness notion of disparate impact for synthetic data generation (SDG), that assesses whether the utility of generated records is the same across sensitive groups.…
cs.LG2025
TAMIS: Tailored Membership Inference Attacks on Synthetic Data
Paul Andrey, Batiste Le Bars, Marc Tommasi
Membership Inference Attacks (MIA) enable to empirically assess the privacy of a machine learning algorithm. In this paper, we propose TAMIS, a novel MIA against differentially-pri…
cs.LG2025
Federated Learning for MRI-based BrainAGE: a multicenter study on post-stroke functional outcome prediction
Vincent Roca, Marc Tommasi, Paul Andrey +8
Brain-predicted age difference (BrainAGE) is a neuroimaging biomarker reflecting brain health. However, training robust BrainAGE models requires large dataset…