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20182026
most citedCommunication-Efficient On-Device Machine Learning: Federated Distillation and Augmentation under Non-IID Private Data

434 citations · 486 across the 7 of their papers we have counts for

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Showing cs.ITShow all

2 papers · 1 filter

cs.IT2022

Asynchronous Decentralized Learning over Unreliable Wireless Networks

Eunjeong Jeong, Matteo Zecchin, Marios Kountouris

Decentralized learning enables edge users to collaboratively train models by exchanging information via device-to-device communication, yet prior works have been limited to wireles…

cs.IT2019★ 29 cited

Distilling On-Device Intelligence at the Network Edge

Jihong Park, Shiqiang Wang, Anis Elgabli +6

Devices at the edge of wireless networks are the last mile data sources for machine learning (ML). As opposed to traditional ready-made public datasets, these user-generated privat…