PostRI computes randomization intervals after differentially private median estimation, delivering 14-850% higher median utility than prior methods while keeping narrow intervals.
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A black-box resampling procedure produces asymptotically valid and tight differentially private nonparametric confidence intervals for arbitrary quantities from any suitable private estimator.
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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.
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Differentially Private Nonparametric Confidence Intervals Under Minimal Distributional Assumptions
A black-box resampling procedure produces asymptotically valid and tight differentially private nonparametric confidence intervals for arbitrary quantities from any suitable private estimator.