Average-Case Averages: Private Algorithms for Smooth Sensitivity and Mean Estimation

6 June 2019

Papers citing "Average-Case Averages: Private Algorithms for Smooth Sensitivity and Mean Estimation"

23 / 23 papers shown

Title
Data-adaptive Differentially Private Prompt Synthesis for In-Context Learning Fengyu Gao Ruida Zhou T. Wang Cong Shen Jing Yang 29 2 0 15 Oct 2024
Distribution-Aware Mean Estimation under User-level Local Differential Privacy Corentin Pla Hugo Richard Maxime Vono FedML 34 0 0 12 Oct 2024
Private Means and the Curious Incident of the Free Lunch Jack Fitzsimons James Honaker Michael Shoemate Vikrant Singhal 37 2 0 19 Aug 2024
Smooth Sensitivity Revisited: Towards Optimality Richard Hladík Jakub Tetek 25 0 0 06 Jul 2024
Smooth Sensitivity for Geo-Privacy Yuting Liang Ke Yi 20 0 0 10 May 2024
Instance-Specific Asymmetric Sensitivity in Differential Privacy David Durfee 21 1 0 02 Nov 2023
The Relative Gaussian Mechanism and its Application to Private Gradient Descent Hadrien Hendrikx Paul Mangold A. Bellet 26 1 0 29 Aug 2023
On the Statistical Complexity of Estimation and Testing under Privacy Constraints Clément Lalanne Aurélien Garivier Rémi Gribonval 25 7 0 05 Oct 2022
Measuring Forgetting of Memorized Training Examples Matthew Jagielski Om Thakkar Florian Tramèr Daphne Ippolito Katherine Lee ... Eric Wallace Shuang Song Abhradeep Thakurta Nicolas Papernot Chiyuan Zhang TDI 47 102 0 30 Jun 2022
New Lower Bounds for Private Estimation and a Generalized Fingerprinting Lemma Gautam Kamath Argyris Mouzakis Vikrant Singhal FedML 34 26 0 17 May 2022
Adaptive Private-K-Selection with Adaptive K and Application to Multi-label PATE Yuqing Zhu Yu-Xiang Wang 22 18 0 30 Mar 2022
Gradient Leakage Attack Resilient Deep Learning Wenqi Wei Ling Liu SILM PILM AAML 15 46 0 25 Dec 2021
FriendlyCore: Practical Differentially Private Aggregation Eliad Tsfadia E. Cohen Haim Kaplan Yishay Mansour Uri Stemmer 20 33 0 19 Oct 2021
Smoothed Differential Privacy Ao Liu Yu-Xiang Wang Lirong Xia 20 0 0 04 Jul 2021
Covariance-Aware Private Mean Estimation Without Private Covariance Estimation Gavin Brown Marco Gaboardi Adam D. Smith Jonathan R. Ullman Lydia Zakynthinou FedML 23 48 0 24 Jun 2021
The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure Aggregation Peter Kairouz Ziyu Liu Thomas Steinke FedML 22 232 0 12 Feb 2021
On Differentially Private Stochastic Convex Optimization with Heavy-tailed Data Di Wang Hanshen Xiao S. Devadas Jinhui Xu 13 55 0 21 Oct 2020
On the Sample Complexity of Privately Learning Unbounded High-Dimensional Gaussians Ishaq Aden-Ali H. Ashtiani Gautam Kamath 40 41 0 19 Oct 2020
CoinPress: Practical Private Mean and Covariance Estimation Sourav Biswas Yihe Dong Gautam Kamath Jonathan R. Ullman 31 113 0 11 Jun 2020
Near Instance-Optimality in Differential Privacy Hilal Asi John C. Duchi 11 38 0 16 May 2020
A Primer on Private Statistics Gautam Kamath Jonathan R. Ullman 33 48 0 30 Apr 2020
Privately Learning High-Dimensional Distributions Gautam Kamath Jerry Li Vikrant Singhal Jonathan R. Ullman FedML 69 148 0 01 May 2018
Differentially Private Chi-Squared Hypothesis Testing: Goodness of Fit and Independence Testing Marco Gaboardi H. Lim Ryan M. Rogers Salil P. Vadhan 45 137 0 07 Feb 2016