Artificial Intelligence Using Federated Learning : Fundamentals, Challenges, and Applications
Book Details
Format
Hardback or Cased Book
ISBN-10
103277164X
ISBN-13
9781032771649
Publisher
Taylor & Francis Ltd
Imprint
CRC Press
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Dec 30th, 2024
Print length
294 Pages
Weight
580 grams
Product Classification:
Coding theory & cryptologyCoding theory and cryptologyProduction and industrial engineeringProduction engineeringElectrical engineeringAutomatic control engineeringDigital and information technologies: Legal aspectsLegal aspects of ITData miningPrivacy & data protectionPrivacy and data protectionSystems analysis & designSystems analysis and designComputer architecture & logic designComputer architecture and logic designArtificial intelligenceArtificial intelligence (AI)
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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.
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.
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