단행본 상세

서지주요정보
Privacy-Preserving Machine Learning
서명 / 저자 Privacy-Preserving Machine Learning [electronic resource] / by Jin Li, Ping Li, Zheli Liu, Xiaofeng Chen, Tong Li.
저자명 Li, Jin. author. aut http://id.loc.gov/vocabulary/relators/aut
Li, Ping. author. aut http://id.loc.gov/vocabulary/relators/aut ; Liu, Zheli. author. (orcid)0000-0002-2984-2661 https://orcid.org/0000-0002-2984-2661 aut http://id.loc.gov/vocabulary/relators/aut ; Chen, Xiaofeng. author. aut http://id.loc.gov/vocabulary/relators/aut ; Li, Tong. author. aut http://id.loc.gov/vocabulary/relators/aut
단체명 SpringerLink (Online service)
판사항 1st ed. 2022.
발행사항 Singapore : Springer Nature Singapore : Imprint: Springer, 2022.
총서명 SpringerBriefs on Cyber Security Systems and Networks, 2522-557X
Online Access https://doi.org/10.1007/978-98... URL

서지기타정보

서지기타정보
ISBN 9789811691393
기타 표준번호 10.1007/978-981-16-9139-3
청구기호 QA76.9.A25
형태사항 VIII, 88 p. 21 illus., 18 illus. in color. online resource.
언어 English
내용 Introduction -- Secure Cooperative Learning in Early Years -- Outsourced Computation for Learning -- Secure Distributed Learning -- Learning with Differential Privacy -- Applications - Privacy-Preserving Image Processing -- Threats in Open Environment -- Conclusion.
주제 Data protection --Law and legislation.
Machine learning.
Privacy.
Machine Learning.
보유판 및 특별호 저록 Springer Nature eBook
Printed edition: 9789811691386 Printed edition: 9789811691409
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