Deep Learning and Federated Architectures for Network Slicing Author

Language: English

Published by Pippet Sky, 2026

9798182704434

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  • New
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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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nach der Bestellung gedruckt Neuware - Printed after ordering - Deep Learning and Federated Architectures for Network Slicing examines artificial intelligence, distributed learning, and modern communication networks. It focuses on deep learning and federated learning architectures for network slicing, a framework that enables logically isolated and adaptable network environments. The discussion covers learning-based approaches to resource management, slice orchestration, traffic analysis, and service-aware optimization. It also considers distributed model training, data privacy, communication efficiency, and coordination across networked devices. The book connects machine learning with wireless communications, software-defined networking, cloud and edge computing, and network virtualization. By bringing these areas together, it provides a focused technical perspective on distributed learning for network slicing. The material is suitable for engineers, researchers, graduate-level readers, and professionals studying intelligent network systems today.…

Seller Inventory # 9798182704434

Title
Deep Learning and Federated Architectures for Network Slicing Author
Author
David Mongol
Publisher
Pippet Sky
Publication year
2026
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 13
9798182704434
Item weight
136 grams
Dimensions
229x152x5 mm

AHA-BUCH GmbH

Einbeck, Germany

5-star seller

AbeBooks seller since August 14, 2006

Shipping rates from Germany to U.S.A.

Item7 to 10 business days5 to 7 business days
First itemUS$ 39.87US$ 51.26
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