113 search results - page 1 / 23 » Computational and Theoretical Analysis of Null Space and Ort... |
JMLR
2006
13 years 4 months ago
2006
Dimensionality reduction is an important pre-processing step in many applications. Linear discriminant analysis (LDA) is a classical statistical approach for supervised dimensiona...
ICML
2006
IEEE
14 years 5 months ago
2006
IEEE
Dimensionality reduction is an important pre-processing step for many applications. Linear Discriminant Analysis (LDA) is one of the well known methods for supervised dimensionali...
ECCV
2004
Springer
13 years 10 months ago
2004
Springer
The null space of the within-class scatter matrix is found to express most discriminative information for the small sample size problem (SSSP). The null space-based LDA takes full ...
CVPR
2004
IEEE
14 years 6 months ago
2004
IEEE
Linear Discriminant Analysis (LDA) is popular feature extraction technique for face recognition. However, it often suffers from the small sample size problem when dealing with the...
FGR
2004
IEEE
13 years 8 months ago
2004
IEEE
The null space-based LDA takes full advantage of the null space while the other methods remove the null space. It proves to be optimal in performance. From the theoretical analysi...