Comments (2)
Thanks for the clarification.
This paper also looks relevant, which suggests specific values for the server-side step size eta.
from federated-learning-in-pytorch.
Dear @bokun-wang,
Hi! Thank you for your interest in my repository. 😃
Exactly as you understood, it is a server momentum, which is firstly proposed in FL by Hsu et al., 2019, coined as FedAvgM
.
This concept has also been adopted into other FL researches, e.g., Dinh et al., 2022 (pFedMe
).
Since vanilla aggregation mechnism is the special case of the momentum verison (i.e.,
Please correct me or PR, if I made an wrong statement or incorrect implementation.
BTW, I think I should explictly add fedavgm
option to the choice of algorithm
argument that forces the momentum constant (i.e.,
Thank you!
Best,
Adam
from federated-learning-in-pytorch.
Related Issues (19)
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