Isbn: 9781032788135 - federated learning for smart communication using iot application (8 risultati)

Condizione: New.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

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

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 .

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.…

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. …

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. …