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The Saddle-Point Accountant for Differential Privacy. (arXiv:2208.09595v1 [cs.CR])
Aug. 23, 2022, 1:20 a.m. | Wael Alghamdi, Shahab Asoodeh, Flavio P. Calmon, Juan Felipe Gomez, Oliver Kosut, Lalitha Sankar, Fei Wei
cs.CR updates on arXiv.org arxiv.org
We introduce a new differential privacy (DP) accountant called the
saddle-point accountant (SPA). SPA approximates privacy guarantees for the
composition of DP mechanisms in an accurate and fast manner. Our approach is
inspired by the saddle-point method -- a ubiquitous numerical technique in
statistics. We prove rigorous performance guarantees by deriving upper and
lower bounds for the approximation error offered by SPA. The crux of SPA is a
combination of large-deviation methods with central limit theorems, which we
derive via …
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