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» Semi-supervised Discriminant Analysis
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CVPR
2006
IEEE
14 years 11 months ago
Selecting Principal Components in a Two-Stage LDA Algorithm
Linear Discriminant Analysis (LDA) is a well-known and important tool in pattern recognition with potential applications in many areas of research. The most famous and used formul...
Aleix M. Martínez, Manli Zhu
KES
2005
Springer
14 years 2 months ago
Feature Generation by Simple FLD
This paper presents a new algorithm for feature generation, which is approximately derived based on geometrical interpretation of the Fisher linear discriminant analysis. In a fiel...
Minoru Fukumi, Yasue Mitsukura
PAMI
2008
153views more  PAMI 2008»
13 years 8 months ago
Correlation Metric for Generalized Feature Extraction
Beyond conventional linear and kernel-based feature extraction, we present a more generalized formulation for feature extraction in this paper. Two representative algorithms using ...
Yun Fu, Shuicheng Yan, Thomas S. Huang
ESWA
2008
124views more  ESWA 2008»
13 years 9 months ago
A hybrid financial analysis model for business failure prediction
Accounting frauds have continuously happened all over the world. This leads to the need of predicting business failures. Statistical methods and machine learning techniques have b...
Shi-Ming Huang, Chih-Fong Tsai, David C. Yen, Yin-...
ICCV
2003
IEEE
14 years 10 months ago
Unified Subspace Analysis for Face Recognition
We propose a face difference model that decomposes face difference into three components, intrinsic difference, transformation difference, and noise. Using the face difference mod...
Xiaogang Wang, Xiaoou Tang