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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…
Iterative Constructions and Private Data Release
Anupam Gupta, Aaron Roth, Jonathan Ullman
In this paper we study the problem of approximately releasing the cut function of a graph while preserving differential privacy, and give new algorithms (and new analyses of existi…
Differentially Private Combinatorial Optimization
Anupam Gupta, Katrina Ligett, Frank McSherry +2
Consider the following problem: given a metric space, some of whose points are "clients", open a set of at most facilities to minimize the average distance from the clients to…