381 citations · 2.3k across the 89 of their papers we have counts for
4 papers · 2 filters
Exploiting Metric Structure for Efficient Private Query Release
Zhiyi Huang, Aaron Roth
We consider the problem of privately answering queries defined on databases which are collections of points belonging to some metric space. We give simple, computationally efficien…
Beyond Worst-Case Analysis in Private Singular Vector Computation
Moritz Hardt, Aaron Roth
We consider differentially private approximate singular vector computation. Known worst-case lower bounds show that the error of any differentially private algorithm must scale pol…
Differential Privacy for the Analyst via Private Equilibrium Computation
Justin Hsu, Aaron Roth, Jonathan Ullman
We give new mechanisms for answering exponentially many queries from multiple analysts on a private database, while protecting differential privacy both for the individuals in the…
Distributed Private Heavy Hitters
Justin Hsu, Sanjeev Khanna, Aaron Roth
In this paper, we give efficient algorithms and lower bounds for solving the heavy hitters problem while preserving differential privacy in the fully distributed local model. In th…