181 search results - page 23 / 37 » Worst-Case Analysis of Selective Sampling for Linear Classif... |
IEEEMM
2007
13 years 7 months ago
2007
— Microarray technology offers a high throughput means to study expression networks and gene regulatory networks in cells. The intrinsic nature of high dimensionality and small s...
CVPR
2005
IEEE
14 years 9 months ago
2005
IEEE
In [1], three popular subspace face recognition methods, PCA, Bayes, and LDA were analyzed under the same framework and an unified subspace analysis was proposed. However, since t...
JCP
2008
13 years 7 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
2004
IEEE
14 years 9 months ago
2004
IEEE
It is well-known that the applicability of Linear Discriminant Analysis (LDA) to high-dimensional pattern classification tasks such as face recognition (FR) often suffers from the...
IJPRAI
2006
13 years 7 months ago
2006
Linear Discriminant Analysis (LDA) is a popular feature extraction technique in statistical pattern recognition. However, it often suffers from the small sample size problem when ...