Convergence Improvement by Parameters Exchange in Asynchronous Decentralized Federated Learning for Non-IID Data

Asato Yamazaki, Takayuki Nishio, Yuko Hara-Azumi. Convergence Improvement by Parameters Exchange in Asynchronous Decentralized Federated Learning for Non-IID Data. In 49th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2023, Durres, Albania, September 6-8, 2023. pages 36-43, IEEE, 2023. [doi]

@inproceedings{YamazakiNH23,
  title = {Convergence Improvement by Parameters Exchange in Asynchronous Decentralized Federated Learning for Non-IID Data},
  author = {Asato Yamazaki and Takayuki Nishio and Yuko Hara-Azumi},
  year = {2023},
  doi = {10.1109/SEAA60479.2023.00015},
  url = {https://doi.org/10.1109/SEAA60479.2023.00015},
  researchr = {https://researchr.org/publication/YamazakiNH23},
  cites = {0},
  citedby = {0},
  pages = {36-43},
  booktitle = {49th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2023, Durres, Albania, September 6-8, 2023},
  publisher = {IEEE},
  isbn = {979-8-3503-4235-2},
}