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AUSAI
2005
Springer
15 years 5 months ago
Resampling LDA/QR and PCA+LDA for Face Recognition
Abstract. Principal Component Analysis (PCA) plus Linear Discriminant Analysis (LDA) (PCA+LDA) and LDA/QR are both two-stage methods that deal with the small sample size (SSS) prob...
Jun Liu, Songcan Chen
SIAMCOMP
2008
140views more  SIAMCOMP 2008»
14 years 11 months ago
The Forgetron: A Kernel-Based Perceptron on a Budget
Abstract. The Perceptron algorithm, despite its simplicity, often performs well in online classification tasks. The Perceptron becomes especially effective when it is used in conju...
Ofer Dekel, Shai Shalev-Shwartz, Yoram Singer
MVA
2000
234views Computer Vision» more  MVA 2000»
14 years 11 months ago
An automatic assessment scheme for steel quality inspection
This paper presents an automatic system for steel quality assessment, by measuring textural properties of carbide distributions. In current steel inspection, specially etched and p...
Klaus Wiltschi, Axel Pinz, Tony Lindeberg
KDD
2001
ACM
192views Data Mining» more  KDD 2001»
16 years 8 days ago
Data mining with sparse grids using simplicial basis functions
Recently we presented a new approach [18] to the classification problem arising in data mining. It is based on the regularization network approach but, in contrast to other method...
Jochen Garcke, Michael Griebel
TKDE
2011
479views more  TKDE 2011»
14 years 6 months ago
Learning Semi-Riemannian Metrics for Semisupervised Feature Extraction
—Discriminant feature extraction plays a central role in pattern recognition and classification. Linear Discriminant Analysis (LDA) is a traditional algorithm for supervised feat...
Wei Zhang, Zhouchen Lin, Xiaoou Tang