论文标题
提出，测试，发布：具有较高概率的差异私人估计
Propose, Test, Release: Differentially private estimation with high probability
论文作者
论文摘要
我们得出了基于Dwork and Lei（2009）引入的“提议，测试，释放”（2009）引入的“提议，测试，释放”（PTR）机制的差异私人中位数和平均估计量的浓度不平等。我们介绍了PTR机制的新常规版本，该版本使我们能够为差异私有估计器得出高概率误差范围。我们的算法为中位数的私人估计提供了第一个统计保证，而均值却没有任何有限的假设，而没有假设目标群体参数在某些已知的有限间隔中。我们的程序不依赖于数据的任何截断，而是为可能重量的尾巴随机变量提供了第一个以下私有中位数和平均值的高概率范围。
We derive concentration inequalities for differentially private median and mean estimators building on the "Propose, Test, Release" (PTR) mechanism introduced by Dwork and Lei (2009). We introduce a new general version of the PTR mechanism that allows us to derive high probability error bounds for differentially private estimators. Our algorithms provide the first statistical guarantees for differentially private estimation of the median and mean without any boundedness assumptions on the data, and without assuming that the target population parameter lies in some known bounded interval. Our procedures do not rely on any truncation of the data and provide the first sub-Gaussian high probability bounds for differentially private median and mean estimation, for possibly heavy tailed random variables.
