On Avoiding the Union Bound When Answering Multiple Differentially Private Queries

16 December 2020

Papers citing "On Avoiding the Union Bound When Answering Multiple Differentially Private Queries"

11 / 11 papers shown

Title
A bounded-noise mechanism for differential privacy Y. Dagan Gil Kur 70 22 0 07 Dec 2020
CoinPress: Practical Private Mean and Covariance Estimation Sourav Biswas Yihe Dong Gautam Kamath Jonathan R. Ullman 53 116 0 11 Jun 2020
Private Mean Estimation of Heavy-Tailed Distributions Gautam Kamath Vikrant Singhal Jonathan R. Ullman 64 99 0 21 Feb 2020
Average-Case Averages: Private Algorithms for Smooth Sensitivity and Mean Estimation Mark Bun Thomas Steinke 61 74 0 06 Jun 2019
Private Hypothesis Selection Mark Bun Gautam Kamath Thomas Steinke Zhiwei Steven Wu 34 90 0 30 May 2019
Privately Learning High-Dimensional Distributions Gautam Kamath Jerry Li Vikrant Singhal Jonathan R. Ullman FedML 81 151 0 01 May 2018
Calibrating Noise to Variance in Adaptive Data Analysis Vitaly Feldman Thomas Steinke 57 48 0 19 Dec 2017
Finite Sample Differentially Private Confidence Intervals Vishesh Karwa Salil P. Vadhan 55 193 0 10 Nov 2017
Between Pure and Approximate Differential Privacy Thomas Steinke Jonathan R. Ullman FedML 68 159 0 24 Jan 2015
Interactive Privacy via the Median Mechanism Aaron Roth Tim Roughgarden 86 283 0 10 Nov 2009
On the Geometry of Differential Privacy Moritz Hardt Kunal Talwar 108 462 0 21 Jul 2009