Robust Federated Learning with Parameter Classification and Weighted Aggregation Against Noisy Labels-Reference-Cited by-同舟云学术

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Robust Federated Learning with Parameter Classification and Weighted Aggregation Against Noisy Labels

Published:2023-12-04 Issue: Volume: Page:2445-2450
ISSN:
Container-title:GLOBECOM 2023 - 2023 IEEE Global Communications Conference
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Author:

Li Qun¹,Duan Congying¹,Chen Siguang¹

Affiliation:

1. School of Internet of Things, Nanjing University of Posts and Telecommunications,Nanjing,China

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Jiangsu Planned Projects for Postdoctoral Research Funds

Postgraduate Research and Innovation Project of Jiangsu Province

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10436708/10436716/10437272.pdf?arnumber=10437272

Reference28 articles.

1. Federated disentangled representation learning for unsupervised brain anomaly detection

2. A Federated Recommender System for Online Services

3. Broadcast Secrecy Rate Maximization in UAV-Empowered IRS Backscatter Communications

4. Challenges of Physical Layer Security in a Satellite-Terrestrial Network

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

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