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Federated Learning

Privacy and Incentive

Produktform: E-Buch Text Elektronisches Buch in proprietärem

This book provides a comprehensive and self-contained introduction to Federated Learning, ranging from the basic knowledge and theories to various key applications, and the privacy and incentive factors are the focus of the whole book. This book is timely needed since Federated Learning is getting popular after the release of the General Data Protection Regulation (GDPR). As Federated Learning aims to enable a machine model to be collaboratively trained without each party exposing private data to others. This setting adheres to regulatory requirements of data privacy protection such as GDPR. weiterlesen

Elektronisches Format: PDF

Sprache(n): Englisch

ISBN: 978-3-030-63076-8 / 978-3030630768 / 9783030630768

Verlag: Springer International Publishing

Erscheinungsdatum: 25.11.2020

Seiten: 286

Herausgegeben von Qiang Yang, Han Yu, Lixin Fan

80,24 € inkl. MwSt.
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