DeceFL: A Principled Decentralized Federated Learning Framework
This repository comprises codes that reproduce experiments in Ye, et al (2021), which has been submitted to Nature Machine Intelligence.
Project Organization
Experiments:
-
Comparative studies of DeceFL and FedAvg, SL on
dataset A2
, provided inDatasetA2/
. -
Time-vary experiments for DeceFL using
dataset A2
- Time-varying graphs with edge changes, provided in
DatasetA2/
- Time-varying graphs with node changes, provided in
NodeVarying/
- Time-varying graphs with edge changes, provided in
-
Comparative study of DeceFL and FedAvg, SL on
CWRU
dataset, provided inCWRU/
. -
An consensus example is generated by scripts in
ConsensusExample/
.
Go to each folder for README.md for every experiment.
Dependencies
Hardware: GPU that supports Pytorch
OS: Linux, Windows 10
Python packages:
torch == 1.9.0
numpy == 1.21.0
sklearn == 0.24.2
pandas == 1.3.1
tqdm == 4.46.0
matplotlib == 3.4.2
More to be filled ...
Reference
[1] Ye Yuan, et al. DeceFL: A Principled Decentralized Federated Learning Framework. Submitted to Nature Machine Intelligence, 2021.