Knowledge Distillation and Training Balance for Heterogeneous Decentralized Multi-Modal Learning Over Wireless Networks-Reference-Cited by-同舟云学术

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Knowledge Distillation and Training Balance for Heterogeneous Decentralized Multi-Modal Learning Over Wireless Networks

Published:2024-10 Issue:10 Volume:23 Page:9629-9644
ISSN:1536-1233
Container-title:IEEE Transactions on Mobile Computing
language:
Short-container-title:IEEE Trans. on Mobile Comput.

Author:

Yin Benshun¹^ORCID,Chen Zhiyong¹^ORCID,Tao Meixia¹^ORCID

Affiliation:

1. Cooperative Medianet Innovation Center and Shanghai Key Laboratory of Digital Media Processing and Transmission, Shanghai Jiao Tong University, Shanghai, China

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7755/10663873/10432997.pdf?arnumber=10432997

Reference53 articles.

1. Deep learning

2. Edge Intelligence: The Confluence of Edge Computing and Artificial Intelligence

3. Toward an Intelligent Edge: Wireless Communication Meets Machine Learning

4. Convergence of Edge Computing and Deep Learning: A Comprehensive Survey

5. Communication-efficient learning of deep networks from decentralized data;McMahan

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. Aggregation Design for Personalized Federated Multi-Modal Learning Over Wireless Networks;IEEE Communications Letters;2024-08

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