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AFLGuard: Byzantine-robust Asynchronous Federated Learning. (arXiv:2212.06325v1 [cs.CR])
Dec. 14, 2022, 2:10 a.m. | Minghong Fang, Jia Liu, Neil Zhenqiang Gong, Elizabeth S. Bentley
cs.CR updates on arXiv.org arxiv.org
Federated learning (FL) is an emerging machine learning paradigm, in which
clients jointly learn a model with the help of a cloud server. A fundamental
challenge of FL is that the clients are often heterogeneous, e.g., they have
different computing powers, and thus the clients may send model updates to the
server with substantially different delays. Asynchronous FL aims to address
this challenge by enabling the server to update the model once any client's
model update reaches it without waiting …
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