From Robustness to Privacy and Back

3 February 2023

Papers citing "From Robustness to Privacy and Back"

10 / 10 papers shown

Title
A Game-theoretic Framework for Privacy-preserving Federated Learning Xiaojin Zhang Lixin Fan Si-Yi Wang Wenjie Li Kai Chen Qiang Yang FedML 21 4 0 11 Apr 2023
Polynomial Time and Private Learning of Unbounded Gaussian Mixture Models Jamil Arbas H. Ashtiani Christopher Liaw 40 23 0 07 Mar 2023
On Private and Robust Bandits Yulian Wu Xingyu Zhou Youming Tao Di Wang 24 5 0 06 Feb 2023
Robustness Implies Privacy in Statistical Estimation Samuel B. Hopkins Gautam Kamath Mahbod Majid Shyam Narayanan 18 49 0 09 Dec 2022
Privacy Induces Robustness: Information-Computation Gaps and Sparse Mean Estimation Kristian Georgiev Samuel B. Hopkins FedML 33 21 0 01 Nov 2022
Analyzing the Differentially Private Theil-Sen Estimator for Simple Linear Regression Jayshree Sarathy Salil P. Vadhan 31 7 0 27 Jul 2022
Private Quantiles Estimation in the Presence of Atoms Clément Lalanne C. Gastaud Nicolas Grislain Aurélien Garivier Rémi Gribonval 17 7 0 15 Feb 2022
Robust and Differentially Private Mean Estimation Xiyang Liu Weihao Kong Sham Kakade Sewoong Oh OOD FedML 53 75 0 18 Feb 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