10 citations · 19 across the 5 of their papers we have counts for
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cs.LG2026
Detectability without Interference: Efficient Canary Design for Privacy Auditing in One Run
Mathieu Dagréou, Aurélien Bellet, Valentin Dorseuil +2
Privacy auditing aims to empirically assess privacy leakage in machine learning models using membership inference attacks (MIAs), and to derive lower bounds on differential privacy…
stat.ML2026
Optimal Transport under Group Fairness Constraints
Linus Bleistein, Mathieu Dagréou, Francisco Andrade +2
Ensuring fairness in matching algorithms is a key challenge in allocating scarce resources and positions. Focusing on Optimal Transport (OT), we introduce a novel notion of group f…