A Multi-view Regularization Method for Semi-supervised Learning

被引：0
|
作者：
Wang, Jiao [1 ]
Luo, Siwei [1 ]
Li, Yan [1 ]
机构：
[1] Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing 100044, Peoples R China
来源：
ADVANCES IN NEURAL NETWORKS - ISNN 2010, PT 1, PROCEEDINGS | 2010年 / 6063卷
关键词：
multi-view learning; semi-supervised learning; regularization; machine learning;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Multi-view semi-supervised learning is a hot research topic recently. In this paper, we consider the regularization problem in multi-view semi-supervised learning. A regularization method adaptive to the given data is proposed, which can use unlabeled data to adjust the degree of regularization automatically. This new regularization method comprises two levels of regularization simultaneously. Experimental evidence on real word dataset shows its effectivity.
引用
收藏
页码：444 / 449
页数：6
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