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Federated Learning Over Wireless Edge Networks - 2022 ed.

By: (Author) Chunyan Miao , (Author) Dusit Niyato , (Author) Jer Shyuan Ng , (Author) Wei Yang Bryan Lim , (Author) Zehui Xiong

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Ksh 16,200.00

Format: Hardback or Cased Book

ISBN-10: 3031078373

ISBN-13: 9783031078378

Edition: 2022 ed.

Series: Wireless Networks

Publisher: Springer International Publishing AG

Imprint: Springer International Publishing AG

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Sep 29th, 2022

Print length: 165 Pages

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This book first presents a tutorial on Federated Learning (FL) and its role in enabling Edge Intelligence over wireless edge networks.

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.


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