Lightweight Protocols for Distributed Private Quantile Estimation
Learning one quantile (such as the median) non-adaptively is as hard as learning the entire CDF, motivating adaptive algorithms for this problem under local and shuffle differential privacy.
Locally Private Histograms in All Privacy Regimes
Improved analysis of existing algorithms for locally private histograms shows optimal error in low-privacy regimes, implying optimal high-privacy algorithms in the shuffle model of differential privacy.