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Ampere: Communication-Efficient and High-Accuracy Split Federated Learning

Zhang, Zihan et al.
arXiv (OAI Expanded) · Papers
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and-cluster-computingdistributedmachine-learningparallel
A Federated Learning (FL) system collaboratively trains neural networks across devices and a server but is limited by significant on-device computation costs. Split Federated Learning (SFL) systems mitigate this by offloading a block of layers of the network from the device to a server. However, in
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