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Apr, 2024
完全分散化神经网络系统中的消失方差问题
Vanishing Variance Problem in Fully Decentralized Neural-Network Systems
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Yongding Tian, Zaid Al-Ars, Maksim Kitsak, Peter Hofstee
TL;DR
去中心化的学习方法federated learning和gossip learning之间的关键区别在于模型聚合方式;我们的研究引入了一种修正方差的模型平均算法,使gossip learning能够达到与federated learning相当的收敛效率。
Abstract
federated learning
and
gossip learning
are emerging methodologies designed to mitigate data privacy concerns by retaining training data on client devices and exclusively sharing locally-trained machine learning (
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