Privacy Preserving Distributed Structure Learning of Probabilistic Graphical Models

被引：0
|
作者：
Li, Husheng [1 ]
机构：
[1] Univ Tennessee, Dept Elect Engn & Comp Sci, Knoxville, TN 37996 USA
来源：
2013 IEEE GLOBECOM WORKSHOPS (GC WKSHPS) | 2013年
关键词：
D O I：
暂无
中图分类号：
TN [电子技术、通信技术];
学科分类号：
0809 ;
摘要：
Privacy preserving structure learning of probabilistic graphical model is studied using the framework of secure multi-party computation. Both constraint and score based learning procedures are rendered the capability of privacy preserving. A data set of adolescent health is used to learn the relationships related to drinking behaviors.
引用
收藏
页码：188 / 193
页数：6
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