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SSPR
2000
Springer
13 years 11 months ago
A New Approximation Method of the Quadratic Discriminant Function
Abstract. For many statistical pattern recognition methods, distributions of sample vectors are assumed to be normal, and the quadratic discriminant function derived from the proba...
Shinichiro Omachi, Fang Sun, Hirotomo Aso
PAMI
2011
13 years 2 months ago
Learning a Family of Detectors via Multiplicative Kernels
—Object detection is challenging when the object class exhibits large within-class variations. In this work, we show that foreground-background classification (detection) and wit...
Quan Yuan, Ashwin Thangali, Vitaly Ablavsky, Stan ...
ICIP
2002
IEEE
14 years 9 months ago
Learning a decision boundary for face detection
This paper describes a pattern classification approach for detecting frontal-view faces via learning a decision boundary. The classification can be achieved either by explicit est...
Tae-Kyun Kim, Donggeon Kong, Sang Ryong Kim
BMCBI
2007
157views more  BMCBI 2007»
13 years 7 months ago
Statistical learning of peptide retention behavior in chromatographic separations: a new kernel-based approach for computational
Background: High-throughput peptide and protein identification technologies have benefited tremendously from strategies based on tandem mass spectrometry (MS/MS) in combination wi...
Nico Pfeifer, Andreas Leinenbach, Christian G. Hub...
SDM
2008
SIAM
150views Data Mining» more  SDM 2008»
13 years 9 months ago
A Stagewise Least Square Loss Function for Classification
This paper presents a stagewise least square (SLS) loss function for classification. It uses a least square form within each stage to approximate a bounded monotonic nonconvex los...
Shuang-Hong Yang, Bao-Gang Hu