Decentralized Deep Learning for Multi-Access Edge Computing.pdf (4.61 MB)

Decentralized Deep Learning for Multi-Access Edge Computing: A Survey on Communication Efficiency and Trustworthiness

preprint

posted on 2021-12-10, 19:07 authored by Yuwei SunYuwei Sun, Hideya Ochiai, Hiroshi Esaki

A survey paper.

History

Email Address of Submitting Author

ywsun@g.ecc.u-tokyo.ac.jp

ORCID of Submitting Author

0000-0001-7315-8034

Submitting Author's Institution

The University of Tokyo

Submitting Author's Country

Japan

Usage metrics

Read the peer-reviewed publication

Decentralized Deep Learning for Multi-Access Edge Computing: A Survey on Communication Efficiency and Trustworthiness

Categories

Keywords

Distributed computing artificial intelligence Edge Computing data privacy threats AI security Trustworthy AI communication efforts Federated Learning decentralized computation

Licence

Exports