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ECCV
2006
Springer
15 years 9 days ago
Extending Kernel Fisher Discriminant Analysis with the Weighted Pairwise Chernoff Criterion
Many linear discriminant analysis (LDA) and kernel Fisher discriminant analysis (KFD) methods are based on the restrictive assumption that the data are homoscedastic. In this paper...
Guang Dai, Dit-Yan Yeung, Hong Chang
ICDM
2009
IEEE
174views Data Mining» more  ICDM 2009»
14 years 5 months ago
Non-sparse Multiple Kernel Learning for Fisher Discriminant Analysis
—We consider the problem of learning a linear combination of pre-specified kernel matrices in the Fisher discriminant analysis setting. Existing methods for such a task impose a...
Fei Yan, Josef Kittler, Krystian Mikolajczyk, Muha...
ICIP
2009
IEEE
14 years 11 months ago
Scale-robust Feature Extraction For Face Recognition
In video surveillance, the sizes of face images are very small. However, few works have been done to investigate scalerobust face recognition. Our experiments on appearancebased m...
GFKL
2005
Springer
105views Data Mining» more  GFKL 2005»
14 years 3 months ago
Variable Selection for Discrimination of More Than Two Classes Where Data are Sparse
In classification, with an increasing number of variables, the required number of observations grows drastically. In this paper we present an approach to put into effect the maxi...
Gero Szepannek, Claus Weihs
NN
2006
Springer
127views Neural Networks» more  NN 2006»
13 years 10 months ago
Assessing self organizing maps via contiguity analysis
- Contiguity Analysis is a straightforward generalization of Linear Discriminant Analysis in which the partition of elements is replaced by a more general graph structure. Applied ...
Ludovic Lebart