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cs.LG2026
DP-KFC: Data-Free Preconditioning for Privacy-Preserving Deep Learning
Marc Molina Van den Bosch, Riccardo Taiello, Albert Sund Aillet +3
Differentially private optimization suffers from a fundamental geometric mismatch: deep networks have highly anisotropic loss landscapes, yet DP-SGD injects isotropic noise. Second…
cs.LG2023★ 11 cited
Fed-BioMed: Open, Transparent and Trusted Federated Learning for Real-world Healthcare Applications
Francesco Cremonesi, Marc Vesin, Sergen Cansiz +16
The real-world implementation of federated learning is complex and requires research and development actions at the crossroad between different domains ranging from data science, t…