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» A Discriminant Analysis for Undersampled Data
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DMIN
2006
134views Data Mining» more  DMIN 2006»
13 years 9 months ago
Hyper-Rectangular and k-Nearest-Neighbor Models in Stochastic Discrimination
The stochastic discrimination (SD) theory considers learning as building models of uniform coverage over data distributions. Despite successful trials of the derived SD method in s...
Iryna Skrypnyk, Tin Kam Ho
PR
2010
186views more  PR 2010»
13 years 6 months ago
Feature extraction by learning Lorentzian metric tensor and its extensions
We develop a supervised dimensionality reduction method, called Lorentzian Discriminant Projection (LDP), for feature extraction and classification. Our method represents the str...
Risheng Liu, Zhouchen Lin, Zhixun Su, Kewei Tang
SCIA
2007
Springer
122views Image Analysis» more  SCIA 2007»
14 years 1 months ago
Individual Discriminative Face Recognition Models Based on Subsets of Features
Abstract. The accuracy of data classification methods depends considerably on the data representation and on the selected features. In this work, the elastic net model selection i...
Line Harder Clemmensen, David Delgado Gomez, Bjarn...
PAMI
2011
13 years 2 months ago
Revisiting Linear Discriminant Techniques in Gender Recognition
—Emerging applications of computer vision and pattern recognition in mobile devices and networked computing require the development of resourcelimited algorithms. Linear classifi...
Juan Bekios-Calfa, José Miguel Buenaposada,...
NIPS
2001
13 years 9 months ago
Discriminative Direction for Kernel Classifiers
In many scientific and engineering applications, detecting and understanding differences between two groups of examples can be reduced to a classical problem of training a classif...
Polina Golland