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IEEEMM
2007
146views more  IEEEMM 2007»
13 years 8 months ago
Learning Microarray Gene Expression Data by Hybrid Discriminant Analysis
— Microarray technology offers a high throughput means to study expression networks and gene regulatory networks in cells. The intrinsic nature of high dimensionality and small s...
Yijuan Lu, Qi Tian, Maribel Sanchez, Jennifer L. N...
CVPR
2005
IEEE
14 years 8 months ago
A Framework of 2D Fisher Discriminant Analysis: Application to Face Recognition with Small Number of Training Samples
A novel framework called 2D Fisher Discriminant Analysis (2D-FDA) is proposed to deal with the Small Sample Size (SSS) problem in conventional One-Dimensional Linear Discriminan...
Hui Kong, Lei Wang, Eam Khwang Teoh, Jian-Gang Wan...
ACCV
2007
Springer
14 years 2 months ago
Kernel Discriminant Analysis Based on Canonical Differences for Face Recognition in Image Sets
A novel kernel discriminant transformation (KDT) algorithm based on the concept of canonical differences is presented for automatic face recognition applications. For each individu...
Wen-Sheng Vincent Chu, Ju-Chin Chen, Jenn-Jier Jam...
ICASSP
2011
IEEE
13 years 10 days ago
Spatially-correlated sensor discriminant analysis
A study of generalization error in signal detection by multiple spatially-distributed and -correlated sensors is provided when the detection rule is learned from a finite number ...
Kush R. Varshney
PAA
2002
13 years 8 months ago
Bagging, Boosting and the Random Subspace Method for Linear Classifiers
: Recently bagging, boosting and the random subspace method have become popular combining techniques for improving weak classifiers. These techniques are designed for, and usually ...
Marina Skurichina, Robert P. W. Duin