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Federated Learning Future Intelligent (16 results)
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Federated Learning for Future Intelligent Wireless Networks
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
Seller rating 5 out of 5 stars
HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Condition: New.
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Condition: As New. Unread book in perfect condition.
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Federated Learning for Future Intelligent Wireless Networks
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Federated Learning for Future Intelligent Wireless Networks
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 102.51
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
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Federated Learning for Future Intelligent Wireless Networks
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
£ 106.79
£ 15 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: As New. Unread book in perfect condition.
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Federated Learning for Future Intelligent Wireless Networks
Language: English
Published by John Wiley & Sons Inc, 2023
ISBN 10: 1119913896 ISBN 13: 9781119913894
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
£ 115.37
£ 17.69 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketHardback. Condition: New. New copy - Usually dispatched within 4 working days.
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Condition: New.
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Condition: New. 1st edition NO-PA16APR2015-KAP.
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Condition: New. Yao Sun, PhD, is a Lecturer with the University of Glasgow in the United Kingdom. He was a former Research Fellow at UESTC in Chengdu, China.Chaoqun You is a Research Fellow at the Singapore University of Technology and Design. She was formerly an Academic .
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Hardcover. Condition: Brand New. 320 pages. 9.02x5.98x0.75 inches. In Stock.
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Buch. Condition: Neu. Neuware - Federated Learning for Future Intelligent Wireless NetworksExplore the concepts, algorithms, and applications underlying federated learningIn Federated Learning for Future Intelligent Wireless Networks, a team of distinguished researchers deliver a robust and insightful collection of resources covering the foundational concepts and algorithms powering federated learning, as well as explanations of how they can be used in wireless communication systems. The editors have included works that examine how communication resource provision affects federated learning performance, accuracy, convergence, scalability, and security and privacy.Readers will explore a wide range of topics that show how federated learning algorithms, concepts, and design and optimization issues apply to wireless communications. Readers will also find:\* A thorough introduction to the fundamental concepts and algorithms of federated learning, including horizontal, vertical, and hybrid FL\* Comprehensive explorations of wireless communication network design and optimization for federated learning\* Practical discussions of novel federated learning algorithms and frameworks for future wireless networks\* Expansive case studies in edge intelligence, autonomous driving, IoT, MEC, blockchain, and content caching and distributionPerfect for electrical and computer science engineers, researchers, professors, and postgraduate students with an interest in machine learning, Federated Learning for Future Intelligent Wireless Networks will also benefit regulators and institutional actors responsible for overseeing and making policy in the area of artificial intelligence.
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Federated Learning for Future Intelligent Wireless Networks
Language: English
Published by John Wiley & Sons Inc, 2023
ISBN 10: 1119913896 ISBN 13: 9781119913894
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
£ 122.35
£ 17.69 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketHardback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
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Federated Learning for Future Intelligent Wireless Networks (Hardcover)
Language: English
Published by John Wiley & Sons Inc, New York, 2023
ISBN 10: 1119913896 ISBN 13: 9781119913894
Hardcover. Condition: new. Hardcover. Federated Learning for Future Intelligent Wireless Networks Explore the concepts, algorithms, and applications underlying federated learning In Federated Learning for Future Intelligent Wireless Networks, a team of distinguished researchers deliver a robust and insightful collection of resources covering the foundational concepts and algorithms powering federated learning, as well as explanations of how they can be used in wireless communication systems. The editors have included works that examine how communication resource provision affects federated learning performance, accuracy, convergence, scalability, and security and privacy. Readers will explore a wide range of topics that show how federated learning algorithms, concepts, and design and optimization issues apply to wireless communications. Readers will also find: A thorough introduction to the fundamental concepts and algorithms of federated learning, including horizontal, vertical, and hybrid FLComprehensive explorations of wireless communication network design and optimization for federated learningPractical discussions of novel federated learning algorithms and frameworks for future wireless networksExpansive case studies in edge intelligence, autonomous driving, IoT, MEC, blockchain, and content caching and distribution Perfect for electrical and computer science engineers, researchers, professors, and postgraduate students with an interest in machine learning, Federated Learning for Future Intelligent Wireless Networks will also benefit regulators and institutional actors responsible for overseeing and making policy in the area of artificial intelligence. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Hardcover. Condition: Brand New. 320 pages. 9.02x5.98x0.75 inches. In Stock. This item is printed on demand.
