Sciweavers

Share
ISNN
2007
Springer

Extensions of Manifold Learning Algorithms in Kernel Feature Space

10 years 8 months ago
Extensions of Manifold Learning Algorithms in Kernel Feature Space
Manifold learning algorithms have been proven to be capable of discovering some nonlinear structures. However, it is hard for them to extend to test set directly. In this paper, a simple yet effective extension algorithm called PIE is proposed. Unlike LPP, which is linear in nature, our method is nonlinear. Besides, our method will never suffer from the singularity problem while LPP and KLPP will. Experimental results of data visualization and classification validate the effectiveness of our proposed method.
Yaoliang Yu, Peng Guan, Liming Zhang
Added 08 Jun 2010
Updated 08 Jun 2010
Type Conference
Year 2007
Where ISNN
Authors Yaoliang Yu, Peng Guan, Liming Zhang
Comments (0)
books