Federated learning smart communication (23 risultati)

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  • Lingua: Inglese

    Editore: Chapman and Hall/CRC, 2026

    1032788135 / 9781032788135

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    Da: California Books, Miami, FL, U.S.A.California Books

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  • Lingua: Inglese

    Editore: Candh/CRC Press, 2026

    1032788135 / 9781032788135

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  • Lingua: Inglese

    Editore: Candh/CRC Press, 2026

    1032788135 / 9781032788135

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    EUR 106,08

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    Paperback. Condizione: Brand New. 274 pages. 6.14x0.62x9.21 inches. In Stock.

  • Lingua: Inglese

    Editore: CRC Press, 2026

    1032788135 / 9781032788135

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    Da: moluna, Greven, Germaniamoluna

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    EUR 79,76

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    Condizione: New. Dr. Kaushal KishorHe received his Ph.D. in Computer science and engineering from AKTU Lucknow, in the domain of Mobile Ad hoc Network. M.Tech &amp B.Tech in Computer Science &amp Engineering from UPTU Lucknow. Currently, he is working in .

  • Lingua: Inglese

    Editore: Taylor & Francis Ltd (Sales) Jul 2026, 2026

    1032788135 / 9781032788135

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    Taschenbuch. Condizione: Neu. Neuware - The effectiveness of federated learning in high¿performance information systems and informatics¿based solutions for addressing current information support requirements is demonstrated in this book. To address heterogeneity challenges in Internet of Things (IoT) contexts, Federated Learning for Smart Communication using IoT Application analyses the development of personalized federated learning algorithms capable of mitigating the detrimental consequences of heterogeneity in several dimensions. It includes case studies of IoT¿based human activity recognition to show the efficacy of personalized federated learning for intelligent IoT applications.Features: - Demonstrates how federated learning offers a novel approach to building personalized models from data without invading users' privacy - Describes how federated learning may assist in understanding and learning from user behavior in IoT applications while safeguarding user privacy - Presents a detailed analysis of current research on federated learning, providing the reader with a broad understanding of the area - Analyses the need for a personalized federated learning framework in cloud¿edge and wireless¿edge architecture for intelligent IoT applications - Comprises real¿life case illustrations and examples to help consolidate understanding of topics presented in each chapter This book is recommended for anyone interested in federated learning¿based intelligent algorithms for smart communications.…

  • Lingua: Inglese

    Editore: Chapman and Hall/CRC, 2024

    1032788127 / 9781032788128

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  • Lingua: Inglese

    Editore: Chapman and Hall/CRC, 2024

    1032788127 / 9781032788128

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  • Lingua: Inglese

    Editore: Chapman and Hall/CRC, 2024

    1032788127 / 9781032788128

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    Da: Majestic Books, Hounslow, Regno UnitoMajestic Books

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  • Lingua: Inglese

    Editore: Chapman and Hall/CRC, 2024

    1032788127 / 9781032788128

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  • Lingua: Inglese

    Editore: Chapman and Hall/CRC, 2024

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  • Lingua: Inglese

    Editore: CRC Press, 2024

    1032788127 / 9781032788128

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  • Lingua: Inglese

    Editore: Chapman and Hall/CRC, 2024

    1032788127 / 9781032788128

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    1032788127 / 9781032788128

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    Editore: Chapman and Hall/CRC, 2024

    1032788127 / 9781032788128

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  • Lingua: Inglese

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    1032788127 / 9781032788128

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  • Lingua: Inglese

    Editore: Chapman and Hall/CRC, 2024

    1032788127 / 9781032788128

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  • Lingua: Inglese

    Editore: Taylor and Francis Ltd, GB, 2024

    1032788127 / 9781032788128

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    Hardback. Condizione: New. The effectiveness of federated learning in high-performance information systems and informatics-based solutions for addressing current information support requirements is demonstrated in this book. To address heterogeneity challenges in Internet of Things (IoT) contexts, Federated Learning for Smart Communication using IoT Application analyses the development of personalized federated learning algorithms capable of mitigating the detrimental consequences of heterogeneity in several dimensions. It includes case studies of IoT-based human activity recognition to show the efficacy of personalized federated learning for intelligent IoT applications.Features:Demonstrates how federated learning offers a novel approach to building personalized models from data without invading users' privacyDescribes how federated learning may assist in understanding and learning from user behavior in IoT applications while safeguarding user privacyPresents a detailed analysis of current research on federated learning, providing the reader with a broad understanding of the areaAnalyses the need for a personalized federated learning framework in cloud-edge and wireless-edge architecture for intelligent IoT applicationsComprises real-life case illustrations and examples to help consolidate understanding of topics presented in each chapterThis book is recommended for anyone interested in federated learning-based intelligent algorithms for smart communications. …

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    Hardcover. Condizione: Brand New. 304 pages. 9.18x6.12x9.21 inches. In Stock.

  • Lingua: Inglese

    Editore: Taylor and Francis Ltd, GB, 2024

    1032788127 / 9781032788128

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    Hardback. Condizione: New. The effectiveness of federated learning in high-performance information systems and informatics-based solutions for addressing current information support requirements is demonstrated in this book. To address heterogeneity challenges in Internet of Things (IoT) contexts, Federated Learning for Smart Communication using IoT Application analyses the development of personalized federated learning algorithms capable of mitigating the detrimental consequences of heterogeneity in several dimensions. It includes case studies of IoT-based human activity recognition to show the efficacy of personalized federated learning for intelligent IoT applications.Features:Demonstrates how federated learning offers a novel approach to building personalized models from data without invading users' privacyDescribes how federated learning may assist in understanding and learning from user behavior in IoT applications while safeguarding user privacyPresents a detailed analysis of current research on federated learning, providing the reader with a broad understanding of the areaAnalyses the need for a personalized federated learning framework in cloud-edge and wireless-edge architecture for intelligent IoT applicationsComprises real-life case illustrations and examples to help consolidate understanding of topics presented in each chapterThis book is recommended for anyone interested in federated learning-based intelligent algorithms for smart communications. …

  • Lingua: Inglese

    Editore: Taylor & Francis Ltd, 2026

    1032788135 / 9781032788135

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    Paperback. Condizione: new. Paperback. The effectiveness of federated learning in highperformance information systems and informaticsbased solutions for addressing current information support requirements is demonstrated in this book. To address heterogeneity challenges in Internet of Things (IoT) contexts, Federated Learning for Smart Communication using IoT Application analyses the development of personalized federated learning algorithms capable of mitigating the detrimental consequences of heterogeneity in several dimensions. It includes case studies of IoTbased human activity recognition to show the efficacy of personalized federated learning for intelligent IoT applications.Features:Demonstrates how federated learning offers a novel approach to building personalized models from data without invading users privacyDescribes how federated learning may assist in understanding and learning from user behavior in IoT applications while safeguarding user privacyPresents a detailed analysis of current research on federated learning, providing the reader with a broad understanding of the areaAnalyses the need for a personalized federated learning framework in cloudedge and wirelessedge architecture for intelligent IoT applicationsComprises reallife case illustrations and examples to help consolidate understanding of topics presented in each chapterThis book is recommended for anyone interested in federated learningbased intelligent algorithms for smart communications. The book aims to demonstrate the effectiveness of federated learning in high-performance information systems and informatics-based solutions for addressing current information support requirements. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. …

  • Lingua: Inglese

    Editore: Taylor & Francis Ltd, 2026

    1032788135 / 9781032788135

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    Paperback. Condizione: new. Paperback. The effectiveness of federated learning in highperformance information systems and informaticsbased solutions for addressing current information support requirements is demonstrated in this book. To address heterogeneity challenges in Internet of Things (IoT) contexts, Federated Learning for Smart Communication using IoT Application analyses the development of personalized federated learning algorithms capable of mitigating the detrimental consequences of heterogeneity in several dimensions. It includes case studies of IoTbased human activity recognition to show the efficacy of personalized federated learning for intelligent IoT applications.Features:Demonstrates how federated learning offers a novel approach to building personalized models from data without invading users privacyDescribes how federated learning may assist in understanding and learning from user behavior in IoT applications while safeguarding user privacyPresents a detailed analysis of current research on federated learning, providing the reader with a broad understanding of the areaAnalyses the need for a personalized federated learning framework in cloudedge and wirelessedge architecture for intelligent IoT applicationsComprises reallife case illustrations and examples to help consolidate understanding of topics presented in each chapterThis book is recommended for anyone interested in federated learningbased intelligent algorithms for smart communications. The book aims to demonstrate the effectiveness of federated learning in high-performance information systems and informatics-based solutions for addressing current information support requirements. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. …

  • Lingua: Inglese

    Editore: CRC Press, 2024

    1032788127 / 9781032788128

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    Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Dr. Kaushal KishorHe received his Ph.D. in Computer science and engineering from AKTU Lucknow, in the domain of Mobile Ad hoc Network. M.Tech &amp B.Tech in Computer Science &amp Engineering from UPTU Lucknow. Currently, he is working in .…