73 citations · 585 across the 58 of their papers we have counts for
3 papers · 2 filters
The Limits of Pan Privacy and Shuffle Privacy for Learning and Estimation
Albert Cheu, Jonathan Ullman
There has been a recent wave of interest in intermediate trust models for differential privacy that eliminate the need for a fully trusted central data collector, but overcome the…
Fair and Useful Cohort Selection
Konstantina Bairaktari, Paul Langton, Huy L. Nguyen +2
A challenge in fair algorithm design is that, while there are compelling notions of individual fairness, these notions typically do not satisfy desirable composition properties, an…
Private Mean Estimation of Heavy-Tailed Distributions
Gautam Kamath, Vikrant Singhal, Jonathan Ullman
We give new upper and lower bounds on the minimax sample complexity of differentially private mean estimation of distributions with bounded -th moments. Roughly speaking, in the…