L-FGADMM: Layer-Wise Federated Group ADMM for Communication Efficient Decentralized Deep Learning Elgabli, Anis, Park, Jihong, Ahmed, Sabbir and Bennis, Mehdi 2020, L-FGADMM: Layer-Wise Federated Group ADMM for Communication Efficient Decentralized Deep Learning, in WCNC 2020 : Proceedings of the 2020 IEEE Wireless Communications and Networking Conference, IEEE, Piscataway, N.J., pp. 1-6, doi: 10.1109/WCNC45663.2020.9120758. Attached Files Name Description MIMEType Size Downloads Title L-FGADMM: Layer-Wise Federated Group ADMM for Communication Efficient Decentralized Deep Learning Author(s) Elgabli, Anis Park, Jihong orcid.org/0000-0001-7623-6552 Ahmed, Sabbir Bennis, Mehdi Conference name Wireless Communications and Networking. Conference (2020 : Seoul, South Korea) Conference location Seoul, South Korea Conference dates 25-28 May. 2020 Title of proceedings WCNC 2020 : Proceedings of the 2020 IEEE Wireless Communications and Networking Conference Publication date 2020 Start page 1 End page 6 Total pages 6 Publisher IEEE Place of publication Piscataway, N.J. Keyword(s) Communication-efficient decentralized machine learning GADMM ADMM federated learning deep learning CORE B ISBN 9781728131061 ISSN 1525-3511 Language eng DOI 10.1109/WCNC45663.2020.9120758 Indigenous content off HERDC Research category E1.1 Full written paper - refereed Persistent URL http://hdl.handle.net/10536/DRO/DU:30140262 Document type: Conference Paper Collections: Faculty of Science, Engineering and Built Environment School of Information Technology Related Links Link Description Connect to published version Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Mon, 20 Jul 2020, 15:02:43 EST Tue, 21 Jul 2020, 05:01:31 EST Tue, 21 Jul 2020, 06:05:04 EST Fri, 24 Jul 2020, 15:11:37 EST Fri, 24 Jul 2020, 15:13:36 EST Fri, 24 Jul 2020, 15:14:21 EST Fri, 24 Jul 2020, 15:36:56 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 30 Abstract Views, 2 File Downloads  -  Detailed Statistics Created: Mon, 20 Jul 2020, 15:02:43 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.