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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Veröffentlicht in:	Proceedings of the International Conference on Distributed Computing Systems S. 300 - 310
Hauptverfasser:	Han, Pengchao, Wang, Shiqiang, Leung, Kin K.
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.11.2020
Schlagworte:	Collaborative work Distributed machine learning edge computing federated learning Finite element analysis gradient sparsification Minimization online learning Optimization Privacy Synchronization Training
ISSN:	2575-8411
Online-Zugang:	Volltext
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