Algorithm

type

Aggregation algorithm.

The input should be:

• fedavg the federated averaging algorithm
• split_learning the Split Learning algorithm
• fedavg_personalized the personalized federated learning algorithm

cross_silo

Whether or not cross-silo training should be used.

total_silos

The total number of silos (edge servers). The input could be any positive integer.

local_rounds

The number of local aggregation rounds on edge servers before sending aggregated weights to the central server. The input could be any positive integer.

fedavg_personalized

Whether or not the personalized training should be used.

local_layer_names

Local layers in a model should remain local at the clients during personalized FL training, and should not be aggregated at the server.

participating_clients_ratio

A float to show the proportion of clients participating in the federated training process. It is under personalization, which is a sub-config path that contains other personalized training parameters.

Default value: 1.0