Federated Learning Over Wireless Edge Networks (Hardcover, 1st ed. 2022)

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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 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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Product Description

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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Product Details

General

Imprint

Springer International Publishing AG

Country of origin

Switzerland

Series

Wireless Networks

Release date

October 2022

Availability

Expected to ship within 10 - 15 working days

First published

2022

Authors

, , , ,

Dimensions

235 x 155mm (L x W)

Format

Hardcover

Pages

165

Edition

1st ed. 2022

ISBN-13

978-3-03-107837-8

Barcode

9783031078378

Categories

LSN

3-03-107837-3



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