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Original paper

Wireless Communications for Collaborative Federated Learning

Volume: 58, Issue: 12, Pages: 48 - 54
Published: Dec 1, 2020
Abstract
To facilitate the deployment of machine learning in resource and privacy-constrained systems such as the Internet of Things, federated learning (FL) has been proposed as a means for enabling edge devices to train a shared learning model while promoting privacy. However, Google's seminal FL algorithm requires all devices to be directly connected with a central controller, which limits its applications. In contrast, this article introduces a novel...
Paper Details
Title
Wireless Communications for Collaborative Federated Learning
Published Date
Dec 1, 2020
Volume
58
Issue
12
Pages
48 - 54
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