Federated learning smart communication (14 Ergebnisse)

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Zustand: 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 .

Taschenbuch. Zustand: 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. …

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Hardback. Zustand: 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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Gebundene Ausgabe. Zustand: Neu. 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. Sprache: Englisch Gewicht in Gramm: 531.

Hardback. Zustand: 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. …