Polynomial Time and Private Learning of Unbounded Gaussian Mixture Models

7 March 2023

Papers citing "Polynomial Time and Private Learning of Unbounded Gaussian Mixture Models"

9 / 9 papers shown

Title
Privacy of SGD under Gaussian or Heavy-Tailed Noise: Guarantees without Gradient Clipping Umut Simsekli Mert Gurbuzbalaban S. Yıldırım Lingjiong Zhu 30 2 0 04 Mar 2024
Private Distribution Learning with Public Data: The View from Sample Compression Shai Ben-David Alex Bie C. Canonne Gautam Kamath Vikrant Singhal 22 11 0 11 Aug 2023
Empirical Bayes inference in sparse high-dimensional generalized linear models Yiqi Tang Ryan Martin 11 3 0 14 Mar 2023
Privacy Induces Robustness: Information-Computation Gaps and Sparse Mean Estimation Kristian Georgiev Samuel B. Hopkins FedML 28 21 0 01 Nov 2022
New Lower Bounds for Private Estimation and a Generalized Fingerprinting Lemma Gautam Kamath Argyris Mouzakis Vikrant Singhal FedML 19 26 0 17 May 2022
A Private and Computationally-Efficient Estimator for Unbounded Gaussians Gautam Kamath Argyris Mouzakis Vikrant Singhal Thomas Steinke Jonathan R. Ullman 50 38 0 08 Nov 2021
Robust and Differentially Private Mean Estimation Xiyang Liu Weihao Kong Sham Kakade Sewoong Oh OOD FedML 37 74 0 18 Feb 2021
On the Sample Complexity of Privately Learning Unbounded High-Dimensional Gaussians Ishaq Aden-Ali H. Ashtiani Gautam Kamath 32 40 0 19 Oct 2020
Privately Learning High-Dimensional Distributions Gautam Kamath Jerry Li Vikrant Singhal Jonathan R. Ullman FedML 52 146 0 01 May 2018