4 papers
Efficient and Optimal Learning of Discrete Distributions with Person-Level Privacy
Gautam Kamath, Mahbod Majid, Ankur Moitra +2
We study learning a discrete distribution under person-level differential privacy in the batched setting. Given users, each contributing i.i.d. samples from an unknown dist…
Robust Statistical Estimators with Bounded Empirical Sensitivity
Valentio Iverson, Gautam Kamath, Argyris Mouzakis +1
We introduce a new measure of robustness for statistical estimators, which we call \emph{empirical sensitivity}. An estimator has bounded empirical sensitivity if, with hi…
Optimal Differentially Private Sampling of Unbounded Gaussians
Valentio Iverson, Gautam Kamath, Argyris Mouzakis
We provide the first -sample algorithm for sampling from unbounded Gaussian distributions under the constraint of $\left(\varepsilon, δ\right…
Private Mean Estimation with Person-Level Differential Privacy
Sushant Agarwal, Gautam Kamath, Mahbod Majid +3
We study person-level differentially private (DP) mean estimation in the case where each person holds multiple samples. DP here requires the usual notion of distributional stabilit…