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Jun, 2023
MimiC: 模仿中央更新,解决联邦学习中客户端掉线的问题
MimiC: Combating Client Dropouts in Federated Learning by Mimicking Central Updates
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Yuchang Sun, Yuyi Mao, Jun Zhang
TL;DR
本文提出 MimiC 算法,针对联邦学习过程中移动设备不稳定可用性导致的模型训练失败的问题,通过修改接收到的模型更新使其模拟中央更新,并通过理论分析和模拟实验证明了该算法的收敛性和优越性。
Abstract
federated learning
(FL) is a promising framework for
privacy-preserving
collaborative learning. In FL, the model training tasks are distributed to clients and only the model updates need to be collected at a cent
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