Efficient Mean Estimation with Pure Differential Privacy via a Sum-of-Squares Exponential Mechanism
@article{Hopkins2021EfficientME, title={Efficient Mean Estimation with Pure Differential Privacy via a Sum-of-Squares Exponential Mechanism}, author={Samuel B. Hopkins and Gautam Kamath and Mahbod Majid}, journal={ArXiv}, year={2021}, volume={abs/2111.12981} }
We give the first polynomial-time algorithm to estimate the mean of a d-variate probability distribution with bounded covariance from Õ(d) independent samples subject to pure differential privacy. Prior algorithms for this problem either incur exponential running time, require Ω(d) samples, or satisfy only the weaker concentrated or approximate differential privacy conditions. In particular, all prior polynomial-time algorithms require d samples to guarantee small privacy loss with…
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