The open-source code of our paper: ''Understanding and Improving Model Averaging in Federated Learning on Heterogeneous Data''. Arxiv: https://arxiv.org/pdf/2305.07845.pdf . IEEE TMC: https://ieeexplore.ieee.org/document/10540229 .
Please run our example Jupiter files directly for your codes.
For the dependency (our codes just use some common packadge) related to our code, please use pip to install the latest version, i.e., pip install 'related dependency package'; e.g., pip install torch. The newest version should be compatible with our code. If you encounter any issues, feel free to raise an issue.
If our code has been helpful to you, we would appreciate a citation as follows:
@ARTICLE {Tailin2024Understanding, author = {T. Zhou and Z. Lin and J. Zhang and D. K. Tsang}, journal = {IEEE Transactions on Mobile Computing}, title = {Understanding and Improving Model Averaging in Federated Learning on Heterogeneous Data}, year = {2024}, volume = {}, number = {01}, issn = {1558-0660}, pages = {1-16}, doi = {10.1109/TMC.2024.3406554}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, month = {may} }