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Distributed Machine Learning and Computing Theory and Applications /

This book focuses on a wide range of distributed machine learning and computing algorithms and their applications in healthcare and engineering systems. The contributors explore how these techniques can be applied to different real-world problems. It is suitable for students and researchers interest...

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Korporativní autor: SpringerLink (Online service)
Další autoři: Amini, M. Hadi (Editor)
Médium: Elektronický zdroj E-kniha
Jazyk:angličtina
Vydáno: Cham : Springer International Publishing : Imprint: Springer, 2024.
Vydání:1st ed. 2024.
Edice:Big and Integrated Artificial Intelligence, 2
Témata:
Telecommunication.
Computational intelligence.
Machine learning.
Cooperating objects (Computer systems).
Communications Engineering, Networks.
Computational Intelligence.
Machine Learning.
Cyber-Physical Systems.
On-line přístup:https://doi.org/10.1007/978-3-031-57567-9
Tagy: Přidat tag
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Obsah:
  • Chapter 1. Distributed Machine Learning and Computing: An Overview
  • Chapter 2. Distributed Multi-agent Meta Learning for Trajectory Design in Wireless Drone Networks
  • Chapter 3. Heterogeneity Aware Distributed Machine Learning at the Wireless Edge for Health IoT Applications: An EEG Data Case Study
  • Chapter 4. A Comprehensive Review of Artificial Intelligence and Machine Learning Methods for Modern Health-care Systems
  • Chapter 5. Vertical Federated Learning: Principles, Applications, and Future Frontiers
  • Chapter 6. Decentralization of Energy Systems with Blockchain: Bridging Top-down and Bottom-up Management of the Electricity Grid.-Chapter 7. Empowering Distributed Solutions in Renewable Energy Systems and Grid Optimization.

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