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Jul, 2023
面向噪声环境的联邦学习收敛性分析与信噪比控制策略的改进
Improved Convergence Analysis and SNR Control Strategies for Federated Learning in the Presence of Noise
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Antesh Upadhyay, Abolfazl Hashemi
TL;DR
本文提出了基于信噪比控制策略的联邦学习收敛率提高方法,并探讨了传输中的非完美通信对联邦学习收敛率的影响,结果发现下行通信噪声对于收敛有更严重的影响。
Abstract
We propose an improved
convergence analysis
technique that characterizes the distributed learning paradigm of
federated learning
(FL) with imperfect/noisy uplink and downlink communications. Such
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