Privately Learning Mixtures of Axis-Aligned Gaussians

3 June 2021

Papers citing "Privately Learning Mixtures of Axis-Aligned Gaussians"

9 / 9 papers shown

Title
Sample-Optimal Locally Private Hypothesis Selection and the Provable Benefits of Interactivity A. F. Pour Hassan Ashtiani S. Asoodeh 51 0 0 09 Dec 2023
Private Distribution Learning with Public Data: The View from Sample Compression Shai Ben-David Alex Bie C. Canonne Gautam Kamath Vikrant Singhal 49 11 0 11 Aug 2023
Polynomial Time and Private Learning of Unbounded Gaussian Mixture Models Jamil Arbas H. Ashtiani Christopher Liaw 45 23 0 07 Mar 2023
New Lower Bounds for Private Estimation and a Generalized Fingerprinting Lemma Gautam Kamath Argyris Mouzakis Vikrant Singhal FedML 47 26 0 17 May 2022
Robust and Differentially Private Mean Estimation Xiyang Liu Weihao Kong Sham Kakade Sewoong Oh OOD FedML 55 75 0 18 Feb 2021
On the Sample Complexity of Privately Learning Unbounded High-Dimensional Gaussians Ishaq Aden-Ali H. Ashtiani Gautam Kamath 46 42 0 19 Oct 2020
List Decodable Subspace Recovery P. Raghavendra Morris Yau 38 25 0 07 Feb 2020
Privately Learning High-Dimensional Distributions Gautam Kamath Jerry Li Vikrant Singhal Jonathan R. Ullman FedML 72 149 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 91 278 0 02 Oct 2017