Convergence of GCM and Its Application to Face Recognition

被引：0

作者：

Li, Kai ^{[1
]}

Chen, Xinyong ^{[1
]}

Yang, Nan ^{[1
]}

Ye, Xiuchen ^{[1
]}

机构：

[1] Hebei Univ, Sch Math & Comp, Baoding 071002, Peoples R China

来源：

ARTIFICIAL INTELLIGENCE AND COMPUTATIONAL INTELLIGENCE, PT I | 2010年 / 6319卷

关键词：

Face recognition; Semi-supervised learning; Kernel matrix; Convergence;

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：

We mainly generalize consistency method in semi-supervised learning by expanding kernel matrix,denoted by GCM(Generalized Consistency Method), and study its convergence. Aimed at GCM,we give the detailed proof for condition of convergence. Moreover,we further study the validity of some variants of GCM. Finally we conduct the experimental study on the parameters involved in GCM to face recognition. Meanwhile, the performance of GCM and its some variants are compared with that of support vector machine methods.

引用

页码：273 / 281

页数：9

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