| 书目名称 | Federated Learning for Wireless Networks | | 编辑 | Choong Seon Hong,Latif U. Khan,Zhu Han | | 视频video | | | 概述 | Offers the first comprehensive and systematic review of federated learning for wireless networks.Describes in detail the key design aspects of federated learning in wireless networks: resource optimiz | | 丛书名称 | Wireless Networks | | 图书封面 |  | | 描述 | .Recently machine learning schemes have attained significant attention as key enablers for next-generation wireless systems. Currently, wireless systems are mostly using machine learning schemes that are based on centralizing the training and inference processes by migrating the end-devices data to a third party centralized location. However, these schemes lead to end-devices privacy leakage. To address these issues, one can use a distributed machine learning at network edge. In this context, federated learning (FL) is one of most important distributed learning algorithm, allowing devices to train a shared machine learning model while keeping data locally. However, applying FL in wireless networks and optimizing the performance involves a range of research topics. For example, in FL, training machine learning models require communication between wireless devices and edge servers via wireless links. Therefore, wireless impairments such as uncertainties among wireless channel states, interference, and noise significantly affect the performance of FL. On the other hand, federated-reinforcement learning leverages distributed computation power and data to solve complex optimization prob | | 出版日期 | Book 2021 | | 关键词 | federated learning; centralized machine learning; distributed machine learning; Internet of Things; FedA | | 版次 | 1 | | doi | https://doi.org/10.1007/978-981-16-4963-9 | | isbn_softcover | 978-981-16-4965-3 | | isbn_ebook | 978-981-16-4963-9Series 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 Singapor |
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发表于 2025-3-21 17:54:45
