Learning in a Large Function Space: Privacy-Preserving Mechanisms for SVM Learning

The ubiquitous need for analyzing privacy-sensitive information—including health records, personal communications, product ratings and social network data—is driving significant interest in privacy-preserving data analysis across several research communities. This paper explores the release of Supp...

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Bibliographic Details
Main Authors: Benjamin I. P. Rubinstein, Peter L. Bartlett, Ling Huang, Nina Taft
Format: Article
Language:English
Published: Labor Dynamics Institute 2012-07-01
Series:The Journal of Privacy and Confidentiality
Subjects:
Online Access:https://journalprivacyconfidentiality.org/index.php/jpc/article/view/612

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