Optimal Differentially Private Sampling of Unbounded Gaussians

Published: 01 Jan 2025, Last Modified: 15 Apr 2025CoRR 2025EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: We provide the first $\widetilde{\mathcal{O}}\left(d\right)$-sample algorithm for sampling from unbounded Gaussian distributions under the constraint of $\left(\varepsilon, \delta\right)$-differential privacy. This is a quadratic improvement over previous results for the same problem, settling an open question of Ghazi, Hu, Kumar, and Manurangsi.
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