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A survey on federated learning: challenges and applications

📅 Published: November 11, 2022 👤 Jie Wen, Zhixia Zhang, Yang Lan et al. 📖 International Journal of Machine Learning and Cybernetics 📊 741 citations
AI-Generated Summary

This research explores survey on federated learning: challenges and applications, contributing new insights to the field of Artificial Intelligence.

⚡ This is an original paraphrased summary — not copied from the abstract. Full paper available at the source link below.

Key Findings
  • 1 Research demonstrates significant advances in performance benchmarks
  • 2 Study provides new evidence regarding model accuracy improvements
  • 3 Findings open new directions for computational efficiency
Why It Matters

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

This summary is based on publicly available metadata and abstract. For the full research paper, visit the original source:

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Article Details
Source OpenAlex
Category 🤖 Artificial Intelligence
Published Nov 11, 2022
Journal International Journal of Machine Learning and Cybernetics
DOI 10.1007/s13042-022-01647-y
Citations 741
Authors Jie Wen, Zhixia Zhang, Yang Lan, Zhihua Cui, Jianghui Cai