HierSFL: Local Differential Privacy-Aided Split Federated Learning in Mobile Edge Computing-Reference-Cited by-同舟云学术

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HierSFL: Local Differential Privacy-Aided Split Federated Learning in Mobile Edge Computing

Published:2023-11-28 Issue: Volume: Page:103-108
ISSN:
Container-title:2023 IEEE Virtual Conference on Communications (VCC)
language:
Short-container-title:

Author:

Quan Minh K.¹,Nguyen Dinh C.²,Nguyen Van-Dinh³,Wijayasundara Mayuri¹,Setunge Sujeeva⁴,Pathirana Pubudu N.¹

Affiliation:

1. School of Engineering, Deakin University,Australia

2. University of Alabama in Huntsville,Department of Electrical and Computer Engineering,USA

3. College of Engineering and Computer Science, VinUniversity,Hanoi,Vietnam,100000

4. School of Engineering, Royal Melbourne Institute of Technology University,Melbourne,VIC,Australia,3000

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10474593/10474603/10474746.pdf?arnumber=10474746

Reference16 articles.

1. Big Data Cleaning Based on Mobile Edge Computing in Industrial Sensor-Cloud

2. Deep reinforcement learning for dynamic computation offloading and resource allocation in cache-assisted mobile edge computing systems

3. When Edge Meets Learning: Adaptive Control for Resource-Constrained Distributed Machine Learning

4. In-Edge AI: Intelligentizing Mobile Edge Computing, Caching and Communication by Federated Learning

5. Hermes

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