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Olive Franzese-McLaughlin

1 accepted papers

2026

Efficient Public Verification of Private ML via Regularization

ICML 2026poster

Training with differential privacy (DP) guarantees dataset members that they cannot be identified by users of the released model. However, those data providers, and, in general, the public, lack methods to efficiently verify that models trained on their data satisfy DP guarantees. The amount of comp…

Cited by 0SourceScholar