PostRI computes randomization intervals after differentially private median estimation, delivering 14-850% higher median utility than prior methods while keeping narrow intervals.
arXiv preprint arXiv:2201.05964 (2022)
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
verdicts
UNVERDICTED 2representative citing papers
Derives a relative disclosure risk indicator (RDR) and algorithms for selecting epsilon in differential privacy based on within-dataset individual risks, plus a multi-query leakage bound.
citing papers explorer
-
Interpreting the Error of Differentially Private Median Queries through Randomization Intervals
PostRI computes randomization intervals after differentially private median estimation, delivering 14-850% higher median utility than prior methods while keeping narrow intervals.
-
Within-Dataset Disclosure Risk for Differential Privacy
Derives a relative disclosure risk indicator (RDR) and algorithms for selecting epsilon in differential privacy based on within-dataset individual risks, plus a multi-query leakage bound.