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
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…
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…