93 search results - page 12 / 19 » Greedy Kernel Principal Component Analysis |
ICA
2004
Springer
2004
Springer
Using Kernel PCA for Initialisation of Variational Bayesian Nonlinear Blind Source Separation Method
14 years 3 months ago
The variational Bayesian nonlinear blind source separation method introduced by Lappalainen and Honkela in 2000 is initialised with linear principal component analysis (PCA). Becau...
PR
2007
13 years 9 months ago
2007
Isomap is one of widely-used low-dimensional embedding methods, where geodesic distances on a weighted graph are incorporated with the classical scaling (metric multidimensional s...
ICIP
2005
IEEE
14 years 11 months ago
2005
IEEE
Robustly tracking moving objects in video sequences is one of the key problems in computer vision. In this paper we introduce a computationally efficient nonlinear kernel learning...
JCP
2008
13 years 9 months ago
2008
kernel canonical correlation analysis (KCCA) is a recently addressed supervised machine learning methods, which shows to be a powerful approach of extracting nonlinear features for...
ICIP
2007
IEEE
14 years 11 months ago
2007
IEEE
Interest in face recognition systems has increased significantly due to the emergence of significant commercial opportunities in surveillance and security applications. In this pa...