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Federated Learning for IoT Applications (EAI/Springer Innovations in Communication and Computing) - Hardcover
- PublisherSpringer
- Publication date2022
- ISBN 10 3030855589
- ISBN 13 9783030855581
- BindingHardcover
- LanguageEnglish
- Edition number1
- Number of pages273
- EditorYadav Satya Prakash, Bhati Bhoopesh Singh, Mahato Dharmendra Prasad, Kumar Sachin
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Federated Learning for IoT Applications
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Springer Nature Switzerland AG, 2022
ISBN 10: 3030855589
ISBN 13: 9783030855581
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Federated Learning for Iot Applications
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Federated Learning for IoT Applications
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ISBN 10: 3030855589
ISBN 13: 9783030855581
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Federated Learning for IoT Applications (EAI/Springer Innovations in Communication and Computing)
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Federated Learning for Iot Applications
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FEDERATED LEARNING FOR IOT APPLICATIONS
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Federated Learning for IoT Applications
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Springer International Publishing Feb 2022, 2022
ISBN 10: 3030855589
ISBN 13: 9783030855581
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents how federated learning helps to understand and learn from user activity in Internet of Things (IoT) applications while protecting user privacy. The authors first show how federated learning provides a unique way to build personalized models using data without intruding on users' privacy. The authors then provide a comprehensive survey of state-of-the-art research on federated learning, giving the reader a general overview of the field. The book also investigates how a personalized federated learning framework is needed in cloud-edge architecture as well as in wireless-edge architecture for intelligent IoT applications. To cope with the heterogeneity issues in IoT environments, the book investigates emerging personalized federated learning methods that are able to mitigate the negative effects caused by heterogeneities in different aspects. The book provides case studies of IoT based human activity recognition to demonstrate the effectiveness of personalized federatedlearning for intelligent IoT applications, as well as multiple controller design and system analysis tools including model predictive control, linear matrix inequalities, optimal control, etc. This unique and complete co-design framework will benefit researchers, graduate students and engineers in the fields of control theory and engineering. 276 pp. Englisch. Seller Inventory # 9783030855581
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