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ICPR
2004
IEEE
14 years 5 months ago
Classification Probability Analysis of Principal Component Null Space Analysis
In a previous paper [1], we have presented a new linear classification algorithm, Principal Component Null Space Analysis (PCNSA) which is designed for problems like object recogn...
Namrata Vaswani, Rama Chellappa
PAKDD
2007
ACM
152views Data Mining» more  PAKDD 2007»
13 years 11 months ago
Spectral Clustering Based Null Space Linear Discriminant Analysis (SNLDA)
While null space based linear discriminant analysis (NLDA) obtains a good discriminant performance, the ability easily suffers from an implicit assumption of Gaussian model with sa...
Wenxin Yang, Junping Zhang
CVPR
2006
IEEE
14 years 6 months ago
Kernel Uncorrelated and Orthogonal Discriminant Analysis: A Unified Approach
Several kernel algorithms have recently been proposed for nonlinear discriminant analysis. However, these methods mainly address the singularity problem in the high dimensional fe...
Tao Xiong, Jieping Ye, Vladimir Cherkassky
CVPR
2000
IEEE
14 years 6 months ago
A Robust and Efficient Motion Segmentation Based on Orthogonal Projection Matrix of Shape Space
A novel algorithm for motion segmentation is proposed. The algorithm uses the fact that shape of an object with homogeneous motion is represented as 4 dimensional linear space. Th...
Naoyuki Ichimura
TKDE
2008
121views more  TKDE 2008»
13 years 4 months ago
Kernel Uncorrelated and Regularized Discriminant Analysis: A Theoretical and Computational Study
Linear and kernel discriminant analyses are popular approaches for supervised dimensionality reduction. Uncorrelated and regularized discriminant analyses have been proposed to ove...
Shuiwang Ji, Jieping Ye