Skip to content

This is the Pytorch code of "Projected Federated Averaging with Heterogeneous Differential Privacy" (VLDB 2022).

License

Notifications You must be signed in to change notification settings

Turningl/PFA_pytorch

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

21 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

PFA_pytorch

This is the source code of paper "Projected Federated Averaging with Heterogeneous Differential Privacy" (accepted by VLDB 2022).

But the original is not this, if you need to see the original, please see https://github.com/Emory-AIMS/PFA

Getting Started

This repository is an implementation of Pytorch version of Federated Averaging (FedAvg), Projected Federated Averaging (PFA) and Projetced Federated Averaging Plus (PFA plus) algorithms.

Install

Pytroch = 1.12.1
Opacus = 1.4.0

Usage

  • NP-FedAvg algorithm:
python main.py --Fedavg=True
  • DP-FedAvg algorithm:
python main.py --Fedavg=True --dp=True
  • PFA algorithm:
python main.py --PFA=True --dp=True
  • PFA plus algorithm:
python main.py --PFA_plus=True --dp=True

Acknowledgements

Contributing

The first author for this job is Junxu Liu. If you have any questions about this article, please contact [email protected]

If you have any questions about this code, please email me [email protected]

About

This is the Pytorch code of "Projected Federated Averaging with Heterogeneous Differential Privacy" (VLDB 2022).

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages