Author

Max Cairney-Leeming

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#artificial intelligence Preprint Sep 2026

A Sharp Transition in Data Reconstruction under Differential Privacy

Data reconstruction attacks have empirically been successful in recovering training samples from learned models, raising privacy concerns and motivating defenses with guarantees that remain valid against future threats. While differential privacy (DP) provides formal protection, choosing the privacy budget remains a ch...

Max Cairney-Leeming, Simone Bombari, Marco Mondelli · 0 citations

#machine learning Preprint May 2026

From Privacy to Generalization: Linear Max-Information Bounds for Differentially Private Learning Algorithms

This work derives explicit upper bounds on the approximate max-information of any algorithm that fulfills $(\epsilon, \delta)$-differential privacy or R\'enyi differential privacy, thereby going beyond the classical results for pure $\epsilon$-differential privacy.

Christoph H. Lampert, Max Cairney-Leeming, Hossein Zakerinia · 0 citations