6 citations · 12 across the 7 of their papers we have counts for
4 papers · 1 filter
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…
Not All Learnable Distribution Classes are Privately Learnable
Mark Bun, Gautam Kamath, Argyris Mouzakis +1
We give an example of a class of distributions that is learnable up to constant error in total variation distance with a finite number of samples, but not learnable under $(\vareps…
New Lower Bounds for Private Estimation and a Generalized Fingerprinting Lemma
Gautam Kamath, Argyris Mouzakis, Vikrant Singhal
We prove new lower bounds for statistical estimation tasks under the constraint of -differential privacy. First, we provide tight lower bounds for private covaria…