Design and Performance Analysis of Partial Computation Output Schemes for Accelerating Coded Machine Learning-Reference-Cited by-同舟云学术

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Design and Performance Analysis of Partial Computation Output Schemes for Accelerating Coded Machine Learning

Published:2023-03-01 Issue:2 Volume:10 Page:1119-1130
ISSN:2327-4697
Container-title:IEEE Transactions on Network Science and Engineering
language:
Short-container-title:IEEE Trans. Netw. Sci. Eng.

Author:

Xu Xinping¹^ORCID,Lin Xiaojun²^ORCID,Duan Lingjie³^ORCID

Affiliation:

1. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore

2. School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA

3. Engineering Systems and Design Pillar, Singapore University of Technology and Design, Singapore

Funder

National Science Foundation

Singapore University of Technology and Design

Academic Research Fund Tier 2

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Control and Systems Engineering

Link

https://ieeexplore.ieee.org/ielam/6488902/10051159/9980435-aam.pdf

Reference35 articles.

1. Gradient coding: Avoiding stragglers in distributed learning;tandon;Proc Int Conf Mach Learn,0

2. Age of Information with Gilbert-Elliot Servers and Samplers

3. Incentive Mechanism Design for Distributed Coded Machine Learning

4. Age-Based Coded Computation for Bias Reduction in Distributed Learning

5. Coded Computation Against Straggling Decoders for Network Function Virtualization

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Coded Federated Learning for Communication-Efficient Edge Computing: A Survey;IEEE Open Journal of the Communications Society;2024

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