Differentially Private Federated Learning with Shuffling and Client Self-Sampling (Conference Paper) | NSF PAGES

skip to main content

An official website of the United States government Here's how you know

Official websites use .gov

A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS

A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Citation Details

Differentially Private Federated Learning with Shuffling and Client Self-Sampling

Award ID(s):: 1740047

PAR ID:: 10313174

Author(s) / Creator(s):: Girgis, Antonious M.; Data, Deepesh; Diggavi, Suhas

Date Published:: 2021-07-12

Journal Name:: IEEE International Symposium on Information Theory (ISIT)

Format(s):: Medium: X

Sponsoring Org:: National Science Foundation

Free Publicly Accessible Full Text
Accepted Manuscript1.0
Conference Paper:
https://doi.org/10.1109/ISIT45174.2021.9517906