| 書目名稱 | Federated Learning Over Wireless Edge Networks |
| 編輯 | Wei Yang Bryan Lim,Jer Shyuan Ng,Chunyan Miao |
| 視頻video | http://file.papertrans.cn/342/341594/341594.mp4 |
| 概述 | Provides a concise introduction to Federated Learning (FL) and how it enables Edge Intelligence.Highlights the challenges inherent to achieving scalable implementation of FL at the wireless edge.Prese |
| 叢書名稱 | Wireless Networks |
| 圖書封面 |  |
| 描述 | .This book first presents a tutorial on Federated Learning (FL) and its role in enabling Edge Intelligence over wireless edge networks. This provides readers with a concise introduction to the challenges and state-of-the-art approaches towards implementing FL over the wireless edge network. Then, in consideration of resource heterogeneity at the network edge, the authors provide multifaceted solutions at the intersection of network economics, game theory, and machine learning towards improving the efficiency of resource allocation for FL over the wireless edge networks. A clear understanding of such issues and the presented theoretical studies will serve to guide practitioners and researchers in implementing resource-efficient FL systems and solving the open issues in FL respectively.. |
| 出版日期 | Book 2022 |
| 關(guān)鍵詞 | Federated Learning; Edge intelligence; Artificial Intelligence; Machine Learning; Edge Computing |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-031-07838-5 |
| isbn_softcover | 978-3-031-07840-8 |
| isbn_ebook | 978-3-031-07838-5Series 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 |
|Archiver|手機(jī)版|小黑屋|
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