332 search results - page 37 / 67 » On the Performance of Chernoff-Distance-Based Linear Dimensi... |
NIPS
2007
14 years 11 months ago
2007
We propose a novel method for linear dimensionality reduction of manifold modeled data. First, we show that with a small number M of random projections of sample points in RN belo...
ICMLA
2007
14 years 11 months ago
2007
Optimal Component Analysis (OCA) is a linear method for feature extraction and dimension reduction. It has been widely used in many applications such as face and object recognitio...
ICMCS
2006
IEEE
15 years 3 months ago
2006
IEEE
It is well-known that supervised learning techniques such as linear discriminant analysis (LDA) often suffer from the so called small sample size problem when apply to solve face ...
DAGM
1997
Springer
15 years 1 months ago
1997
Springer
Using the 3-dimensional structure tensor, dense displacement vector fields (DVF) can be computed with subpixel accuracy. The approach is based on the detection of linear symmetrie...
MCS
2000
Springer
15 years 1 months ago
2000
Springer
Abstract Investigating a data set of the critical size makes a classification task difficult. Studying dissimilarity data refers to such a problem, since the number of samples equa...