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Federated Learning: Foundations and Applications

Edited by Rajkumar Buyya, Edited by Anwesha Mukherjee, Edited by Sajal K Das

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normal price: R 7 422.95

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Federated Learning: Foundations and Applications provides a comprehensive guide to the foundations, architectures, systems, security, privacy, and applications of federated learning. Sections cover fundamental concepts, including machine learning, deep learning, centralized learning, and distributed learning processes. The book then progresses to coverage of the architectures, algorithms, and system models of Federated Learning, as well as security, privacy, and energy-efficiency techniques. Finally, the book presents various applications of Federated Learning through real-world case studies, illustrating both centralized and decentralized Federated Learning. Federated Learning has become an increasingly important machine learning technique because it introduces local data analysis within clients and requires exchange of only model parameters between clients and servers, hence the addition of this new release is ideal for those interested in the topics presented.

| product details |



Normally shipped | Forthcoming. We are not accepting backorders for this item yet
Publisher | Elsevier Science & Technology
Published date | 29 May 2026
Language |
Format | Paperback / softback
Pages | 366
Dimensions | 276 x 216 x 0mm (L x W x H)
Weight | 450g
ISBN | 978-0-4434-4433-3
Readership Age |
BISAC | computers / artificial intelligence


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