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Publicado por Springer Nature Switzerland AG, 2022
ISBN 10: 3030855589 ISBN 13: 9783030855581
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Publicado por Springer Nature Switzerland AG, 2022
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Publicado por Springer Nature Switzerland AG, CH, 2022
ISBN 10: 3030855589 ISBN 13: 9783030855581
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Añadir al carritoCondición: New. 1st ed. 2022 edition NO-PA16APR2015-KAP.
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Publicado por Springer, Berlin|Springer International Publishing|Springer, 2021
ISBN 10: 3030855589 ISBN 13: 9783030855581
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Añadir al carritoCondición: New. This book presents how federated learning helps to understand and learn from user activity in Internet of Things (IoT) applications while protecting user privacy.This book presents how federated learning helps to understand and learn from user activity .
Idioma: Inglés
Publicado por Springer International Publishing, Springer International Publishing, 2022
ISBN 10: 3030855589 ISBN 13: 9783030855581
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Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.
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Añadir al carritoHardcover. Condición: Brand New. 273 pages. 9.25x6.10x0.69 inches. In Stock.
Idioma: Inglés
Publicado por Springer Nature Switzerland, Springer International Publishing Feb 2022, 2022
ISBN 10: 3030855589 ISBN 13: 9783030855581
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
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Añadir al carritoBuch. Condición: Neu. 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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 276 pp. Englisch.
Idioma: Inglés
Publicado por Springer Nature Switzerland AG, CH, 2022
ISBN 10: 3030855589 ISBN 13: 9783030855581
Librería: Rarewaves.com UK, London, Reino Unido
EUR 145,10
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Añadir al carritoHardback. Condición: New. 2022 ed.
Idioma: Inglés
Publicado por Springer International Publishing Feb 2022, 2022
ISBN 10: 3030855589 ISBN 13: 9783030855581
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 128,39
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Añadir al carritoBuch. Condición: 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.
Librería: Revaluation Books, Exeter, Reino Unido
EUR 142,95
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Añadir al carritoHardcover. Condición: Brand New. 273 pages. 9.25x6.10x0.69 inches. In Stock. This item is printed on demand.
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Librería: Biblios, Frankfurt am main, HESSE, Alemania
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