arXiv:2611.01218v1 Announce Type: new Abstract: Gaussian differential privacy (GDP) and zero-concentrated differential privacy (zCDP) are two competing privacy accounting frameworks, but they share similar minimax lower bounds in various estimation problems. Moreover, it is known that a mechanism satisfying $\mu$-GDP satisfies $(\mu^2/2)$-zCDP, whereas the converse fails to hold at the same calibration.
Optimal Conversion from Zero-Concentrated to Gaussian Differential Privacy
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