Adaptive Gradient Sparsification for Efficient Federated Learning: An Online Learning Approach

Federated learning (FL) is an emerging technique for training machine learning models using geographically dispersed data collected by local entities. It includes local computation and synchronization steps. To reduce the communication overhead and improve the overall efficiency of FL, gradient spar...

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Vydané v:	Proceedings of the International Conference on Distributed Computing Systems s. 300 - 310
Hlavní autori:	Han, Pengchao, Wang, Shiqiang, Leung, Kin K.
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.11.2020
Predmet:	Collaborative work Distributed machine learning edge computing federated learning Finite element analysis gradient sparsification Minimization online learning Optimization Privacy Synchronization Training
ISSN:	2575-8411
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