2 citations · 2 across the 1 of their papers we have counts for
4 papers
Program Analysis for Adaptive Data Analysis
Jiawen Liu, Weihao Qu, Marco Gaboardi +2
Data analyses are usually designed to identify some property of the population from which the data are drawn, generalizing beyond the specific data sample. For this reason, data an…
Online Matrix Factorization, Online Private Query Release, and Online Discrepancy Minimization
Aleksandar Nikolov, Haohua Tang, Jonathan Ullman
In this paper we consider several related online computation problems. First, we study answering sequences of statistical queries arriving online, and being answered immediately wh…
CoinPress: Practical Private Mean and Covariance Estimation
Sourav Biswas, Yihe Dong, Gautam Kamath +1
We present simple differentially private estimators for the mean and covariance of multivariate sub-Gaussian data that are accurate at small sample sizes. We demonstrate the effect…
Lower Bounds for Public-Private Learning under Distribution Shift
Amrith Setlur, Pratiksha Thaker, Jonathan Ullman
The most effective differentially private machine learning algorithms in practice rely on an additional source of purportedly public data. This paradigm is most interesting when th…