arvintashakori / SemiPFL

SemiPFL: Personalized Semi-Supervised Federated Learning Framework for Edge Intelligence

SemiPFL: Personalized Semi-Supervised Federated Learning Framework for Edge Intelligence

This is an official implementation of SemiPFL paper. [Link]

Published in IEEE Internet of Things Journal, 2023 [Link]

Installation

• Create a virtual environment with conda/virtualenv
• Clone the repo
• Run: cd <PATH_TO_THE_CLONED_REPO>
• Run: pip install -e . to install necessary packages and path links.

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Reproduce Paper Results

• Upload datasets to Datasets
• Run: cd Scripts
• Run: python semipfl.py

Bibtex

If you find this code useful in your research, please cite:

@article{tashakori2023semipfl,
  title={SemiPFL: personalized semi-supervised federated learning framework for edge intelligence},
  author={Tashakori, Arvin and Zhang, Wenwen and Wang, Z Jane and Servati, Peyman},
  journal={IEEE Internet of Things Journal},
  year={2023},
  publisher={IEEE}
}