Communication Efficient Framework for Decentralized Machine Learning

Elgabli, Anis, Park, Jihong, Bedi, Amrit S, Bennis, Mehdi and Aggarwal, Vaneet 2020, Communication Efficient Framework for Decentralized Machine Learning, in CISS 2020 : Proceedings of the Information Sciences and Systems 2020 conference, Institute of Electrical and Electronics Engineers, Piscataway, N.J., pp. 1-5, doi: 10.1109/CISS48834.2020.1570627384.

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Title Communication Efficient Framework for Decentralized Machine Learning
Author(s) Elgabli, Anis
Park, JihongORCID iD for Park, Jihong orcid.org/0000-0001-7623-6552
Bedi, Amrit S
Bennis, Mehdi
Aggarwal, Vaneet
Conference name IEEE Information Theory Society. Conference (54th. 2020 : Princeton, N.J.)
Conference location Princeton, NJ, USA
Conference dates 2020/03/18 - 2020/03/20
Title of proceedings CISS 2020 : Proceedings of the Information Sciences and Systems 2020 conference
Publication date 2020
Start page 1
End page 5
Total pages 5
Publisher Institute of Electrical and Electronics Engineers
Place of publication Piscataway, N.J.
Keyword(s) data privacy
gradient methods
learning (artificial intelligence)
regression analysis
topology
CORE C
Notes Conference cancelled due to COVID-19
ISBN 9781728140858
Language eng
DOI 10.1109/CISS48834.2020.1570627384
Indigenous content off
HERDC Research category E1.1 Full written paper - refereed
Persistent URL http://hdl.handle.net/10536/DRO/DU:30139694

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