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May, 2024
将先见之明修剪与零阶优化结合:低内存设备上高效的联邦学习
When Foresight Pruning Meets Zeroth-Order Optimization: Efficient Federated Learning for Low-Memory Devices
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Pengyu Zhang, Yingjie Liu, Yingbo Zhou, Xiao Du, Xian Wei...
TL;DR
基于神经切向核(NTK)的联邦预见修剪方法可以与联邦 BP-Free 训练框架无缝集成,减少内存使用并提高性能。
Abstract
Although
federated learning
(FL) enables collaborative learning in Artificial Intelligence of Things (
aiot
) design, it fails to work on low-memory
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