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Federated Learning: Principles, Paradigms, and Applications
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Federated Learning: Principles, Paradigms, and Applications
Explains federated learning and how it integrates AI technologies allowing multiple collaborators to build a robust machine-learning model using a large dataset. Describes benefits of federated learning, covering data privacy, data security, data access rights etc. Analyses common challenges, and attack strategies affecting FL systems.
321 pages, 7 Illustrations, color; 72 Illustrations, black and white
| Media | Books Hardcover Book (Book with hard spine and cover) |
| Released | September 20, 2024 |
| ISBN13 | 9781774916384 |
| Publishers | Apple Academic Press Inc. |
| Pages | 334 |
| Dimensions | 150 × 220 × 20 mm · 680 g |
| Language | English |
| Editor | Nair, Akarsh K. |
| Editor | Ouaissa, Mariya |
| Editor | Sahoo, Jayakrushna |
