Theoretical Guarantees for Model Auditing with Finite Adversaries

Mario Diaz, Peter Kairouz, Jiachun Liao +1

Privacy concerns have led to the development of privacy-preserving approaches for learning models from sensitive data. Yet, in practice, even models learned with privacy guarantees…