Federated Learning for Healthcare Applications
Author:
Affiliation:
1. School of Artificial Intelligence, Guilin University of Electronic Technology, Guilin, China
2. Laboratory for Imagery, Vision and Artificial Intelligence, Ecole de Technologie Superieure, Montreal, Canada
Funder
Guilin Innovation Platform and Talent Program
Guangxi Science and Technology Base and Talent Project
National Natural Science Foundation of China
National Innovation Training Program for College Students
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing
Link
http://xplorestaging.ieee.org/ielx7/6488907/6702522/10288131.pdf?arnumber=10288131
Cited by 10 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. Client-Side Gradient Inversion Attack in Federated Learning Using Secure Aggregation;IEEE Internet of Things Journal;2024-09-01
2. Two-Phase Sparsification With Secure Aggregation for Privacy-Aware Federated Learning;IEEE Internet of Things Journal;2024-08-15
3. Analysis of Federated Learning Paradigm in Medical Domain: Taking COVID-19 as an Application Use Case;Applied Sciences;2024-05-11
4. A Multifaceted Survey on Federated Learning: Fundamentals, Paradigm Shifts, Practical Issues, Recent Developments, Partnerships, Trade-Offs, Trustworthiness, and Ways Forward;IEEE Access;2024
5. Client Evaluation and Revision in Federated Learning: Towards Defending Free-Riders and Promoting Fairness;Lecture Notes in Computer Science;2024
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