Privacy-Preserving Restricted Boltzmann Machine
Joint Authors
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-06-23
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
With the arrival of the big data era, it is predicted that distributed data mining will lead to an information technology revolution.
To motivate different institutes to collaborate with each other, the crucial issue is to eliminate their concerns regarding data privacy.
In this paper, we propose a privacy-preserving method for training a restricted boltzmann machine (RBM).
The RBM can be got without revealing their private data to each other when using our privacy-preserving method.
We provide a correctness and efficiency analysis of our algorithms.
The comparative experiment shows that the accuracy is very close to the original RBM model.
American Psychological Association (APA)
Li, Yu& Zhang, Yuan& Ji, Yue. 2014. Privacy-Preserving Restricted Boltzmann Machine. Computational and Mathematical Methods in Medicine،Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-448771
Modern Language Association (MLA)
Li, Yu…[et al.]. Privacy-Preserving Restricted Boltzmann Machine. Computational and Mathematical Methods in Medicine No. 2014 (2014), pp.1-7.
https://search.emarefa.net/detail/BIM-448771
American Medical Association (AMA)
Li, Yu& Zhang, Yuan& Ji, Yue. Privacy-Preserving Restricted Boltzmann Machine. Computational and Mathematical Methods in Medicine. 2014. Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-448771
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-448771