The Cost of Privacy: Optimal Rates of Convergence for Parameter Estimation with Differential Privacy

12 Feb 2019 T. Tony Cai Yichen Wang Linjun Zhang

Privacy-preserving data analysis is a rising challenge in contemporary statistics, as the privacy guarantees of statistical methods are often achieved at the expense of accuracy. In this paper, we investigate the tradeoff between statistical accuracy and privacy in mean estimation and linear regression, under both the classical low-dimensional and modern high-dimensional settings... (read more)

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