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Author

Marco Mondelli

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#machine learning Preprint Sep 2026

When do data mixtures improve scaling laws? Insights from high-dimensional regression

Modern machine learning systems are trained on mixtures of data from different domains, and choosing the right mixture can substantially improve downstream performance. Despite an extensive literature on data mixing and reweighting, existing work is largely empirical and it remains unclear when auxiliary data genuinely...

Di-Yuan Wu, Le-Han Chen, Theodor Misiakiewicz et al. · 0 citations
#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

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