Parallel and Memory-Efficient Distributed Edge Learning in B5G IoT Networks-Reference-Cited by-同舟云学术

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Parallel and Memory-Efficient Distributed Edge Learning in B5G IoT Networks

Published:2023-01 Issue:1 Volume:17 Page:222-233
ISSN:1932-4553
Container-title:IEEE Journal of Selected Topics in Signal Processing
language:
Short-container-title:IEEE J. Sel. Top. Signal Process.

Author:

Zhao Jianxin¹^ORCID,Vandenhove Pierre²^ORCID,Xu Peng¹,Tao Hao³,Wang Liang⁴^ORCID,Liu Chi Harold¹^ORCID,Crowcroft Jon⁴^ORCID

Affiliation:

1. School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China

2. F.R.S.-FNRS, UMONS - Université de Mons, Mons, Belgium

3. China Ship Development and Design Center, Wuhan, China

4. University of Cambridge, Cambridge, U.K.

Funder

National Defence Basic Scientific Research

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/4200690/10050192/09956889.pdf?arnumber=9956889

Reference45 articles.

1. Energy Efficient Federated Learning Over Wireless Communication Networks

2. Parallelizing Backpropagation Neural Network Using MapReduce and Cascading Model

3. A joint learning and communications framework for federated learning over wireless networks;chen;IEEE Trans Wireless Commun,2021

4. Parallel back-propagation neural network training technique using CUDA on multiple GPUs

5. Sideways: Depth-Parallel Training of Video Models

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