Computing Tight Differential Privacy Guarantees Using FFT

Antti Koskela, Joonas Jälkö, Antti Honkela

Differentially private (DP) machine learning has recently become popular. The privacy loss of DP algorithms is commonly reported using $(\epsilon ,\delta )$-DP. In this paper, we propo…