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Artificial Intelligence Using Federated Learning: Fundamentals, Challenges, and Applications - Intelligent Manufacturing and Industrial Engineering
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Artificial Intelligence Using Federated Learning: Fundamentals, Challenges, and Applications - Intelligent Manufacturing and Industrial Engineering
Federated machine learning is a novel approach to combining distributed machine learning, cryptography, security, and incentive mechanism design. It allows organizations to keep sensitive and private data on users or customers decentralized and secure, helping them comply with stringent data protection regulations like GDPR and CCPA.
344 pages, 37 Tables, black and white; 84 Line drawings, black and white; 9 Halftones, black and whi
| Media | Bøker Innbunden bok (Bok med hard rygg og stivt omslag) |
| Utgitt | 30. desember 2024 |
| ISBN13 | 9781032771649 |
| Utgivere | Taylor & Francis Ltd |
| Antall sider | 294 |
| Mål | 150 × 220 × 20 mm · 580 g |
| Språk | Engelsk |
| Redaktør | Balas, Valentina E. (Aurel Vlaicu University of Arad and Romanian Academy of Scientists, Romania) |
| Redaktør | Elngar, Ahmed A (Beni-Suef Uni.) |
| Redaktør | Oliva, Diego (University de Guadalajara, Mexico) |
