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Differentially Privacy-Preserving Federated Learning Using Wasserstein Generative Adversarial Network

Version 3 2024-10-18, 07:08
Version 2 2024-05-30, 16:19
Version 1 2022-02-04, 08:27
conference contribution
posted on 2024-10-18, 07:08 authored by Y Wan, Y Qu, L Gao, Yong XiangYong Xiang
Differentially Privacy-Preserving Federated Learning Using Wasserstein Generative Adversarial Network

History

Volume

2021-September

Pagination

1-6

Location

Athens, Greece

Start date

2021-09-05

End date

2021-09-08

ISSN

1530-1346

eISSN

2642-7389

ISBN-13

9781665427449

Language

eng

Publication classification

E1 Full written paper - refereed

Title of proceedings

ISCC 2021 : Proceedings of the 2021 IEEE Symposium on Computers and Communications

Event

Computers and Communications. Symposium (2021 : Athens, Greece)

Publisher

IEEE

Place of publication

Piscataway, N.J.

Series

IEEE Symposium on Computers and Communications ISCC

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