Abstract:
|
Differential privacy has emerged as a strong model to reason about privacy in a formal manner. However, performing statistical inference under the constraint of differential privacy is not well developed. In this talk, we will present work on developing differentially private estimators that are also optimal for statistical inference. We will study the fundamental limits of differential privacy for statistical inference and present practical differentially private algorithms that achieve this limit.
|