New Lower Bounds for Private Estimation and a Generalized Fingerprinting Lemma

17 May 2022

Papers citing "New Lower Bounds for Private Estimation and a Generalized Fingerprinting Lemma"

21 / 21 papers shown

Title
Tukey Depth Mechanisms for Practical Private Mean Estimation Gavin Brown Lydia Zakynthinou 39 0 0 25 Feb 2025
Learning with Differentially Private (Sliced) Wasserstein Gradients Clément Lalanne Jean-Michel Loubes David Rodríguez-Vítores FedML 41 0 0 03 Feb 2025
Dimension-free Private Mean Estimation for Anisotropic Distributions Yuval Dagan Michael I. Jordan Xuelin Yang Lydia Zakynthinou Nikita Zhivotovskiy 37 2 0 01 Nov 2024
Distribution Learnability and Robustness Shai Ben-David Alex Bie Gautam Kamath Tosca Lechner 32 2 0 25 Jun 2024
Lower Bounds for Private Estimation of Gaussian Covariance Matrices under All Reasonable Parameter Regimes V. S. Portella Nick Harvey 16 3 0 26 Apr 2024
Private Gradient Descent for Linear Regression: Tighter Error Bounds and Instance-Specific Uncertainty Estimation Gavin Brown Krishnamurthy Dvijotham Georgina Evans Daogao Liu Adam D. Smith Abhradeep Thakurta 34 3 0 21 Feb 2024
Better and Simpler Lower Bounds for Differentially Private Statistical Estimation Shyam Narayanan FedML 19 9 0 10 Oct 2023
Mixtures of Gaussians are Privately Learnable with a Polynomial Number of Samples Mohammad Afzali H. Ashtiani Christopher Liaw 24 5 0 07 Sep 2023
Concentrated Differential Privacy for Bandits Achraf Azize D. Basu 26 4 0 01 Sep 2023
Smooth Lower Bounds for Differentially Private Algorithms via Padding-and-Permuting Fingerprinting Codes Naty Peter Eliad Tsfadia Jonathan R. Ullman 34 4 0 14 Jul 2023
Improving the Utility of Differentially Private Clustering through Dynamical Processing Junyoung Byun Yujin Choi Jaewoo Lee 9 1 0 27 Apr 2023
A Polynomial Time, Pure Differentially Private Estimator for Binary Product Distributions Vikrant Singhal 29 9 0 13 Apr 2023
Polynomial Time and Private Learning of Unbounded Gaussian Mixture Models Jamil Arbas H. Ashtiani Christopher Liaw 40 23 0 07 Mar 2023
Fast, Sample-Efficient, Affine-Invariant Private Mean and Covariance Estimation for Subgaussian Distributions Gavin Brown Samuel B. Hopkins Adam D. Smith FedML 19 17 0 28 Jan 2023
Privately Estimating a Gaussian: Efficient, Robust and Optimal Daniel Alabi Pravesh Kothari Pranay Tankala Prayaag Venkat Fred Zhang 64 0 0 15 Dec 2022
Robustness Implies Privacy in Statistical Estimation Samuel B. Hopkins Gautam Kamath Mahbod Majid Shyam Narayanan 11 49 0 09 Dec 2022
Differentially Private Covariance Revisited Wei Dong Yuting Liang K. Yi FedML 10 13 0 28 May 2022
DP-PCA: Statistically Optimal and Differentially Private PCA Xiyang Liu Weihao Kong Prateek Jain Sewoong Oh 27 21 0 27 May 2022
A Private and Computationally-Efficient Estimator for Unbounded Gaussians Gautam Kamath Argyris Mouzakis Vikrant Singhal Thomas Steinke Jonathan R. Ullman 50 39 0 08 Nov 2021
On the Sample Complexity of Privately Learning Unbounded High-Dimensional Gaussians Ishaq Aden-Ali H. Ashtiani Gautam Kamath 37 41 0 19 Oct 2020
Privately Learning High-Dimensional Distributions Gautam Kamath Jerry Li Vikrant Singhal Jonathan R. Ullman FedML 66 148 0 01 May 2018