most citedTo Talk or to Work: Flexible Communication Compression for Energy Efficient Federated Learning over Heterogeneous Mobile Edge Devices

12 citations · 12 across the 1 of their papers we have counts for

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cs.LG2020★ 12 cited

To Talk or to Work: Flexible Communication Compression for Energy Efficient Federated Learning over Heterogeneous Mobile Edge Devices

Liang Li, Dian Shi, Ronghui Hou +3

Recent advances in machine learning, wireless communication, and mobile hardware technologies promisingly enable federated learning (FL) over massive mobile edge devices, which ope…