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Privacy-Preserving Deep Learning: A Comprehensive Survey - SpringerBriefs on Cyber Security Systems and Networks Kwangjo Kim 2021 edition
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Privacy-Preserving Deep Learning: A Comprehensive Survey - SpringerBriefs on Cyber Security Systems and Networks
Kwangjo Kim
This book discusses the state-of-the-art in privacy-preserving deep learning (PPDL), especially as a tool for machine learning as a service (MLaaS), which serves as an enabling technology by combining classical privacy-preserving and cryptographic protocols with deep learning.
74 pages, 14 Illustrations, color; 7 Illustrations, black and white; XIV, 74 p. 21 illus., 14 illus.
| Media | Boeken Paperback Book (Boek met zachte kaft en gelijmde rug) |
| Vrijgegeven | 23 juli 2021 |
| ISBN13 | 9789811637636 |
| Uitgevers | Springer Verlag, Singapore |
| Pagina's | 74 |
| Afmetingen | 150 × 220 × 10 mm · 152 g |
![Cover for Kwangjo Kim · Network Intrusion Detection using Deep Learning: A Feature Learning Approach - SpringerBriefs on Cyber Security Systems and Networks (Paperback Book) [2018 edition] (2018)](https://imusic.b-cdn.net/images/item/original/438/9789811314438.jpg?kwangjo-kim-2018-network-intrusion-detection-using-deep-learning-a-feature-learning-approach-springerbriefs-on-cyber-security-systems-and-networks-paperback-book&class=scaled&v=1541782700)
