Privacy for free in the overparameterized regime

IO_AdminUncategorized1 month ago23 Views

Proceedings of the National Academy of Sciences, Volume 122, Issue 15, April 2025.
SignificanceIn many deep learning applications, training datasets routinely include personal, sensitive information. Learning from these data is possible without creating privacy infringement via methods guaranteeing differential privacy, designed to …
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