FedFaSt: Selective Federated Learning Using Fittest Parameters Aggregation and Slotted Clients Training

Ferdinand Kahenga, Antoine B. Bagula, Sajal K. Das. FedFaSt: Selective Federated Learning Using Fittest Parameters Aggregation and Slotted Clients Training. In IEEE Global Communications Conference, GLOBECOM 2023, Kuala Lumpur, Malaysia, December 4-8, 2023. pages 3879-3884, IEEE, 2023. [doi]

@inproceedings{KahengaBD23,
  title = {FedFaSt: Selective Federated Learning Using Fittest Parameters Aggregation and Slotted Clients Training},
  author = {Ferdinand Kahenga and Antoine B. Bagula and Sajal K. Das},
  year = {2023},
  doi = {10.1109/GLOBECOM54140.2023.10437003},
  url = {https://doi.org/10.1109/GLOBECOM54140.2023.10437003},
  researchr = {https://researchr.org/publication/KahengaBD23},
  cites = {0},
  citedby = {0},
  pages = {3879-3884},
  booktitle = {IEEE Global Communications Conference, GLOBECOM 2023, Kuala Lumpur, Malaysia, December 4-8, 2023},
  publisher = {IEEE},
  isbn = {979-8-3503-1090-0},
}