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TKAGFL: A Federated Communication Framework Under Data heterogeneity

  • Published:2022 Issue: Volume: Page:1-1
  • ISSN:2327-4697
  • Container-title:IEEE Transactions on Network Science and Engineering
  • language:
  • Short-container-title:IEEE Trans. Netw. Sci. Eng.

Author:

Pei Jiaming1,Yu Zhi2,Li Jinhai3,Jan Mian Ahmad4,Lakshmanna Kuruva5

Affiliation:

1. School of Computer Science, The University of Sydney, Camperdown, NSW 2006, Australia

2. Chongqing University, 400044, Chongqing, China

3. Taizhou University, 225300 Taizhou, Jiangsu, China

4. Abdul Wali Khan University Mardan, Mardan, Pakistan

5. School of Information Technology and Engineering, Vellore Institute of Technology, 632014, India

Funder

Humanity and Social Science Youth foundation of Ministry of Education of China

Social Development Project

Scientific Research Foundation of Taizhou University

the Qinglan Project of Jiangsu Universities University-Industry Collaborative Education Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

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

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2. A Cross-Client Coordinator in Federated Learning Framework for Conquering Heterogeneity;IEEE Transactions on Neural Networks and Learning Systems;2024

3. A lightweight energy consumption ensemble-based botnet detection model for IoT/6G networks;Sustainable Energy Technologies and Assessments;2023-12

4. Intelligent speech recognition algorithm in multimedia visual interaction via BiLSTM and attention mechanism;Neural Computing and Applications;2023-11-29

5. Boosted federated learning based on improved Particle Swarm Optimization for healthcare IoT devices;Computers in Biology and Medicine;2023-09
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