Fast-Convergent Federated Learning

Federated learning has emerged recently as a promising solution for distributing machine learning tasks through modern networks of mobile devices. Recent studies have obtained lower bounds on the expected decrease in model loss that is achieved through each round of federated learning. However, conv...

Full description

Saved in:

Bibliographic Details
Published in:	IEEE journal on selected areas in communications 2021-01, Vol.39 (1), p.201-218
Main Authors:	Nguyen, Hung T., Sehwag, Vikash, Hosseinalipour, Seyyedali, Brinton, Christopher G., Chiang, Mung, Vincent Poor, H.
Format:	Article
Language:	English
Subjects:	Algorithms Cognitive tasks Collaborative work Computational modeling Convergence Data models distributed optimization Electronic devices fast convergence rate Federated learning Heterogeneity Lower bounds Machine learning Model accuracy Optimization Performance evaluation Sampling Servers Wireless networks
Citations:	Items that this one cites Items that cite this one
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!