A Primer on Private Statistics
Machine Learning
2020-05-04 v1 Cryptography and Security
Data Structures and Algorithms
Information Theory
Machine Learning
math.IT
Abstract
Differentially private statistical estimation has seen a flurry of developments over the last several years. Study has been divided into two schools of thought, focusing on empirical statistics versus population statistics. We suggest that these two lines of work are more similar than different by giving examples of methods that were initially framed for empirical statistics, but can be applied just as well to population statistics. We also provide a thorough coverage of recent work in this area.
Cite
@article{arxiv.2005.00010,
title = {A Primer on Private Statistics},
author = {Gautam Kamath and Jonathan Ullman},
journal= {arXiv preprint arXiv:2005.00010},
year = {2020}
}
Comments
20 pages. Comments welcome