Data Heterogeneity-Robust Federated Learning via Group Client Selection in Industrial IoT. (arXiv:2202.01512v1 [cs.LG])

Nowadays, the industrial Internet of Things (IIoT) has played an integral
role in Industry 4.0 and produced massive amounts of data for industrial
intelligence. These data locate on decentralized devices in modern factories.
To protect the confidentiality of industrial data, federated learning (FL) was
introduced to collaboratively train shared machine learning models. However,
the local data collected by different devices skew in class distribution and
degrade industrial FL performance. This challenge has been widely studied at
the mobile edge, but …

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