書目名稱 | Communication Efficient Federated Learning for Wireless Networks |
編輯 | Mingzhe Chen,Shuguang Cui |
視頻video | http://file.papertrans.cn/231/230395/230395.mp4 |
概述 | Offers a comprehensive and systematic book on design of federated learning.Provides key approaches for optimizing performance of federated learning.Demonstrates effective applications of federated lea |
叢書名稱 | Wireless Networks |
圖書封面 |  |
描述 | .This book provides a comprehensive study of?Federated Learning (FL) over wireless networks. It consists of?three main parts: (a) Fundamentals and preliminaries of?FL, (b) analysis and optimization of?FL over wireless networks, and (c) applications of wireless FL for Internet-of-Things systems. In particular, in the first part, the authors provide a detailed overview on widely-studied FL framework. In the?second part of?this book, the?authors comprehensively discuss three key wireless techniques including wireless resource management, quantization, and over-the-air computation to?support the?deployment of?FL over realistic wireless networks. It also presents several solutions based on?optimization theory, graph theory and machine learning to?optimize the?performance of?FL over wireless networks. In the?third part of?this book, the?authors introduce the?use of?wireless FL algorithms for autonomous vehicle control and mobile edge computing optimization.?.Machine learning and data-driven approaches have recently received considerable attention as key enablers for next-generation intelligent networks. Currently, most existing learning solutions for wireless networks rely on centralizin |
出版日期 | Book 2024 |
關鍵詞 | Distributed learning; Federated learning; Resource Allocation; Quantization; Over the air computation; Au |
版次 | 1 |
doi | https://doi.org/10.1007/978-3-031-51266-7 |
isbn_softcover | 978-3-031-51268-1 |
isbn_ebook | 978-3-031-51266-7Series ISSN 2366-1186 Series E-ISSN 2366-1445 |
issn_series | 2366-1186 |
copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |