Supporting data for “Optimizing Federated Learning with Communication Reduction and Synchronization Control”

Experimental data used in Thesis “Optimizing Federated Learning with Communication Reduction and Synchronization Control”. There are source codes that read the logs from the 'data/' folder and then display the figures or tables. <br> This thesis aims to improve the federated learning systems with communication reduction techniques and accelerate model convergence speed by asynchronous training. The provided data show the effectiveness of our proposed algorithm, which includes two fast K asynchronous algorithms and a novel weighted aggregation function. <br> <br> <br>