105 citations · 108 across the 7 of their papers we have counts for
7 papers
Differentially Private Synthetic High-dimensional Tabular Stream
Girish Kumar, Thomas Strohmer, Roman Vershynin
While differentially private synthetic data generation has been explored extensively in the literature, how to update this data in the future if the underlying private data changes…
Metric geometry of the privacy-utility tradeoff
March Boedihardjo, Thomas Strohmer, Roman Vershynin
Synthetic data are an attractive concept to enable privacy in data sharing. A fundamental question is how similar the privacy-preserving synthetic data are compared to the true dat…
Online Differentially Private Synthetic Data Generation
Yiyun He, Roman Vershynin, Yizhe Zhu
We present a polynomial-time algorithm for online differentially private synthetic data generation. For a data stream within the hypercube and an infinite time horizon, w…
An Algorithm for Streaming Differentially Private Data
Girish Kumar, Thomas Strohmer, Roman Vershynin
Much of the research in differential privacy has focused on offline applications with the assumption that all data is available at once. When these algorithms are applied in practi…
Differentially Private Low-dimensional Synthetic Data from High-dimensional Datasets
Yiyun He, Thomas Strohmer, Roman Vershynin +1
Differentially private synthetic data provide a powerful mechanism to enable data analysis while protecting sensitive information about individuals. However, when the data lie in a…
Private measures, random walks, and synthetic data
March Boedihardjo, Thomas Strohmer, Roman Vershynin
Differential privacy is a mathematical concept that provides an information-theoretic security guarantee. While differential privacy has emerged as a de facto standard for guarante…