CoinPress: Practical Private Mean and Covariance Estimation

11 June 2020

Papers citing "CoinPress: Practical Private Mean and Covariance Estimation"

23 / 23 papers shown

Title
Private Means and the Curious Incident of the Free Lunch Jack Fitzsimons James Honaker Michael Shoemate Vikrant Singhal 37 2 0 19 Aug 2024
Better Gaussian Mechanism using Correlated Noise Christian Janos Lebeda 36 2 0 13 Aug 2024
On Differentially Private U Statistics Kamalika Chaudhuri Po-Ling Loh Shourya Pandey Purnamrita Sarkar FedML 54 0 0 06 Jul 2024
Sample-Optimal Locally Private Hypothesis Selection and the Provable Benefits of Interactivity A. F. Pour Hassan Ashtiani S. Asoodeh 38 0 0 09 Dec 2023
Instance-Specific Asymmetric Sensitivity in Differential Privacy David Durfee 21 1 0 02 Nov 2023
Differentially Private Aggregation via Imperfect Shuffling Badih Ghazi Ravi Kumar Pasin Manurangsi Jelani Nelson Samson Zhou FedML 30 1 0 28 Aug 2023
Polynomial Time and Private Learning of Unbounded Gaussian Mixture Models Jamil Arbas H. Ashtiani Christopher Liaw 40 23 0 07 Mar 2023
A Fast Algorithm for Adaptive Private Mean Estimation John C. Duchi Saminul Haque Rohith Kuditipudi FedML 24 15 0 17 Jan 2023
Differentially Private Bootstrap: New Privacy Analysis and Inference Strategies Zhanyu Wang Guang Cheng Jordan Awan 18 9 0 12 Oct 2022
On the Statistical Complexity of Estimation and Testing under Privacy Constraints Clément Lalanne Aurélien Garivier Rémi Gribonval 25 7 0 05 Oct 2022
Privacy Aware Experimentation over Sensitive Groups: A General Chi Square Approach R. Friedberg Ryan M. Rogers 21 3 0 17 Aug 2022
Private Estimation with Public Data Alex Bie Gautam Kamath Vikrant Singhal 30 28 0 16 Aug 2022
Private independence testing across two parties Praneeth Vepakomma M. Amiri C. Canonne Ramesh Raskar Alex Pentland 26 2 0 08 Jul 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
Private High-Dimensional Hypothesis Testing Shyam Narayanan FedML 30 11 0 03 Mar 2022
Differentially Private Regression with Unbounded Covariates Jason Milionis Alkis Kalavasis Dimitris Fotakis Stratis Ioannidis 23 10 0 19 Feb 2022
Differential Privacy Over Riemannian Manifolds M. Reimherr Karthik Bharath Carlos Soto 27 17 0 03 Nov 2021
FriendlyCore: Practical Differentially Private Aggregation Eliad Tsfadia E. Cohen Haim Kaplan Yishay Mansour Uri Stemmer 20 33 0 19 Oct 2021
Differentially Private Aggregation in the Shuffle Model: Almost Central Accuracy in Almost a Single Message Badih Ghazi Ravi Kumar Pasin Manurangsi Rasmus Pagh Amer Sinha FedML 57 36 0 27 Sep 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
On the Sample Complexity of Privately Learning Unbounded High-Dimensional Gaussians Ishaq Aden-Ali H. Ashtiani Gautam Kamath 40 41 0 19 Oct 2020
Privately Learning High-Dimensional Distributions Gautam Kamath Jerry Li Vikrant Singhal Jonathan R. Ullman FedML 69 148 0 01 May 2018
Prochlo: Strong Privacy for Analytics in the Crowd Andrea Bittau Ulfar Erlingsson Petros Maniatis Ilya Mironov A. Raghunathan David Lie Mitch Rudominer Ushasree Kode J. Tinnés B. Seefeld 83 278 0 02 Oct 2017