arxiv
PublishedSeptember 1, 2026 at 4:00 AM
Revisiting the Provable-Auditable Privacy Gap of DP-SGD
Publisher summary· verbatim
arXiv:2608.28934v1 Announce Type: new Abstract: Differential privacy (DP) has traditionally been used to provide theoretical upper bounds on an algorithm's stability to changing its training data. In modern private machine learning applications, achieving strong tradeoffs between utility and theoret
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Originally published on arxiv ↗