FedGA: A greedy approach to enhance federated learning with Non-IID data-Reference-Cited by-同舟云学术

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FedGA: A greedy approach to enhance federated learning with Non-IID data

Published:2024-10 Issue: Volume:301 Page:112201
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Cong Yue,Zeng Yuxiang,Qiu Jing^ORCID,Fang Zhongyang,Zhang Lejun^ORCID,Cheng Du,Liu Jia,Tian Zhihong^ORCID

Funder

National Major Science and Technology Projects of China

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference32 articles.

1. Intelligent machinery fault diagnosis with event-based camera;Li;IEEE Trans. Ind. Inform.,2023

2. Dynamic vision enabled contactless cross-domain machine fault diagnosis with neuromorphic computing;Chen;IEEE/CAA J. Autom. Sin.,2024

3. J. Lu, H. Zuo, G. Zhang, Fuzzy multiple-source transfer learning, IEEE Trans. Fuzzy Syst. 28 (12) 3418–3431.

4. Communication-efficient learning of deep networks from decentralized data;McMahan,2017

5. Federated learning with non-IID data;Zhao,2018

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