v1v2 (latest)

Better and Simpler Lower Bounds for Differentially Private Statistical Estimation

10 October 2023

Papers citing "Better and Simpler Lower Bounds for Differentially Private Statistical Estimation"

27 / 27 papers shown

Title
Private Statistical Estimation via Truncation Manolis Zampetakis Felix Zhou 84 0 0 18 May 2025
Lower Bounds for Private Estimation of Gaussian Covariance Matrices under All Reasonable Parameter Regimes V. S. Portella Nick Harvey 80 5 0 26 Apr 2024
Smooth Lower Bounds for Differentially Private Algorithms via Padding-and-Permuting Fingerprinting Codes Naty Peter Eliad Tsfadia Jonathan R. Ullman 79 5 0 14 Jul 2023
Score Attack: A Lower Bound Technique for Optimal Differentially Private Learning T. Tony Cai Yichen Wang Linjun Zhang 66 19 0 13 Mar 2023
A Fast Algorithm for Adaptive Private Mean Estimation John C. Duchi Saminul Haque Rohith Kuditipudi FedML 59 15 0 17 Jan 2023
Robustness Implies Privacy in Statistical Estimation Samuel B. Hopkins Gautam Kamath Mahbod Majid Shyam Narayanan 78 52 0 09 Dec 2022
Differentially Private Covariance Revisited Wei Dong Yuting Liang K. Yi FedML 65 14 0 28 May 2022
New Lower Bounds for Private Estimation and a Generalized Fingerprinting Lemma Gautam Kamath Argyris Mouzakis Vikrant Singhal FedML 75 29 0 17 May 2022
Private Robust Estimation by Stabilizing Convex Relaxations Pravesh Kothari Pasin Manurangsi A. Velingker 60 47 0 07 Dec 2021
A Private and Computationally-Efficient Estimator for Unbounded Gaussians Gautam Kamath Argyris Mouzakis Vikrant Singhal Thomas Steinke Jonathan R. Ullman 84 40 0 08 Nov 2021
Tight and Robust Private Mean Estimation with Few Users Cheng-Han Chiang Vahab Mirrokni Hung-yi Lee FedML 55 30 0 22 Oct 2021
FriendlyCore: Practical Differentially Private Aggregation Eliad Tsfadia E. Cohen Haim Kaplan Yishay Mansour Uri Stemmer 78 36 0 19 Oct 2021
Covariance-Aware Private Mean Estimation Without Private Covariance Estimation Gavin Brown Marco Gaboardi Adam D. Smith Jonathan R. Ullman Lydia Zakynthinou FedML 65 50 0 24 Jun 2021
Instance-optimal Mean Estimation Under Differential Privacy Ziyue Huang Yuting Liang K. Yi 55 57 0 01 Jun 2021
Learning with User-Level Privacy Daniel Levy Ziteng Sun Kareem Amin Satyen Kale Alex Kulesza M. Mohri A. Suresh FedML 70 90 0 23 Feb 2021
Robust and Differentially Private Mean Estimation Xiyang Liu Weihao Kong Sham Kakade Sewoong Oh OOD FedML 76 77 0 18 Feb 2021
On the Sample Complexity of Privately Learning Unbounded High-Dimensional Gaussians Ishaq Aden-Ali H. Ashtiani Gautam Kamath 113 43 0 19 Oct 2020
A Primer on Private Statistics Gautam Kamath Jonathan R. Ullman 87 48 0 30 Apr 2020
Differentially Private Assouad, Fano, and Le Cam Jayadev Acharya Ziteng Sun Huanyu Zhang FedML 62 60 0 14 Apr 2020
Private Mean Estimation of Heavy-Tailed Distributions Gautam Kamath Vikrant Singhal Jonathan R. Ullman 81 100 0 21 Feb 2020
Private Stochastic Convex Optimization with Optimal Rates Raef Bassily Vitaly Feldman Kunal Talwar Abhradeep Thakurta 78 246 0 27 Aug 2019
Private Hypothesis Selection Mark Bun Gautam Kamath Thomas Steinke Zhiwei Steven Wu 62 91 0 30 May 2019
The Cost of Privacy: Optimal Rates of Convergence for Parameter Estimation with Differential Privacy T. Tony Cai Yichen Wang Linjun Zhang 68 169 0 12 Feb 2019
Privately Learning High-Dimensional Distributions Gautam Kamath Jerry Li Vikrant Singhal Jonathan R. Ullman FedML 90 151 0 01 May 2018
Finite Sample Differentially Private Confidence Intervals Vishesh Karwa Salil P. Vadhan 60 194 0 10 Nov 2017
Tight Lower Bounds for Differentially Private Selection Thomas Steinke Jonathan R. Ullman 86 75 0 10 Apr 2017
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 216 6,155 0 01 Jul 2016