论文标题
多数投票投票给分布式私人标志选择
Majority Vote for Distributed Differentially Private Sign Selection
论文作者
论文摘要
近年来，保护隐私数据分析变得更加普遍。在这项研究中，我们提出了一个分布式组差异性多数票投票机制，以在分布式设置中的标志选择问题。为此，我们将迭代剥离应用于稳定性函数，并使用指数机制恢复符号。为了增强适用性，我们研究了分布式系统中的平均估计和线性回归问题的私人标志选择。我们的方法与非私有场景一样，以最佳的信噪比恢复了支持和标志，这比私人变量选择的现代作品更好。此外，符号选择一致性是通过理论保证证明的。进行了模拟研究以证明所提出的方法的有效性。
Privacy-preserving data analysis has become more prevalent in recent years. In this study, we propose a distributed group differentially private Majority Vote mechanism, for the sign selection problem in a distributed setup. To achieve this, we apply the iterative peeling to the stability function and use the exponential mechanism to recover the signs. For enhanced applicability, we study the private sign selection for mean estimation and linear regression problems, in distributed systems. Our method recovers the support and signs with the optimal signal-to-noise ratio as in the non-private scenario, which is better than contemporary works of private variable selections. Moreover, the sign selection consistency is justified by theoretical guarantees. Simulation studies are conducted to demonstrate the effectiveness of the proposed method.
