5 papers
Private Graph Property Testing
Hendrik Fichtenberger, Abigail Gentle, Tamalika Mukherjee +1
Graph property testing asks whether a massive graph satisfies a given property, or is far from doing so, using only a sublinear number of queries to the graph. Since property teste…
Uniformity Testing under User-Level Local Privacy
Clément L. Canonne, Abigail Gentle, Vikrant Singhal
We initiate the study of distribution testing under \emph{user-level} local differential privacy, where each of users contributes samples from the unknown underlying distri…
Necessity of Block Designs for Optimal Locally Private Distribution Estimation
Abigail Gentle
Local differential privacy represents the gold standard for preserving the privacy of data before it leaves the device, and distribution estimation under this model has been well s…
Lightweight Protocols for Distributed Private Quantile Estimation
Anders Aamand, Fabrizio Boninsegna, Abigail Gentle +2
Distributed data analysis is a large and growing field driven by a massive proliferation of user devices, and by privacy concerns surrounding the centralised storage of data. We co…
Locally Private Histograms in All Privacy Regimes
Clément L. Canonne, Abigail Gentle
Frequency estimation, a.k.a. histograms, is a workhorse of data analysis, and as such has been thoroughly studied under differentially privacy. In particular, computing histograms…