CoinPress: Practical Private Point Estimation and Confidence Intervals
Gautam Kamath · Feb 26, 2021
Date: 2021-02-26
Time: 15:30-16:30 (Montreal time)
Zoom Link
Meeting ID: 843 0865 5572
Passcode: 690084
Abstract:
We consider point estimation and generation of confidence intervals under the constraint of differential privacy. We provide a simple and practical framework for these tasks in relatively general settings. Our investigation addresses a novel challenge that arises in the differentially private setting, which involves the cost of weak a priori bounds on the parameters of interest. This framework is applied to the problems of Gaussian mean and covariance estimation. Despite the simplicity of our method, we are able to achieve minimax near-optimal rates for these problems. Empirical evaluations, on the problems of mean estimation, covariance estimation, and principal component analysis, demonstrate significant improvements in comparison to previous work.