5.3 Algorithm - FedAvgM

Implement Federated Averaging with Server Momentum (FedAvgM) algorithm[1].

Parameters

• factors (str, optional) - aggregation weight mode (default: "weighted")
  • "weighted": weighted average based on the size of local datasets
  • "arithmetic": arithmetic average
  • "self-defined": weighted average according to user-defined weights
• lr (float, optional) - learning rate (default: 0.3)
• momentum (float, optional) - momentum factor (default: 0.9)
• lr_decay_rate (float, optional) - learning rate decay factor (default: 1)
• lr_decay_step (int, optional) - period of learning rate decay. (default: 100)
  
  

Reference

[1] Hsu, Tzu-Ming Harry, Hang Qi, and Matthew Brown. "Measuring the effects of non-identical data distribution for federated visual classification." arXiv preprint arXiv:1909.06335 (2019).

The user interface of FedAvgM algorithm: