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Federated Learning for Future Intelligent Wireless Networks

Lei Zhang editor Gang Feng editor Yao Sun editor Chaoqun You editor

Format:Hardback

Publisher:John Wiley & Sons Inc

Published:28th Nov '23

£110.00

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Federated Learning for Future Intelligent Wireless Networks cover

Federated Learning for Future Intelligent Wireless Networks

Explore the concepts, algorithms, and applications underlying federated learning

In Federated Learning for Future Intelligent Wireless Networks, a team of distinguished researchers deliver a robust and insightful collection of resources covering the foundational concepts and algorithms powering federated learning, as well as explanations of how they can be used in wireless communication systems. The editors have included works that examine how communication resource provision affects federated learning performance, accuracy, convergence, scalability, and security and privacy.

Readers will explore a wide range of topics that show how federated learning algorithms, concepts, and design and optimization issues apply to wireless communications. Readers will also find:

  • A thorough introduction to the fundamental concepts and algorithms of federated learning, including horizontal, vertical, and hybrid FL
  • Comprehensive explorations of wireless communication network design and optimization for federated learning
  • Practical discussions of novel federated learning algorithms and frameworks for future wireless networks
  • Expansive case studies in edge intelligence, autonomous driving, IoT, MEC, blockchain, and content caching and distribution

Perfect for electrical and computer science engineers, researchers, professors, and postgraduate students with an interest in machine learning, Federated Learning for Future Intelligent Wireless Networks will also benefit regulators and institutional actors responsible for overseeing and making policy in the area of artificial intelligence.

ISBN: 9781119913894

Dimensions: unknown

Weight: 694g

320 pages