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» Training Linear Discriminant Analysis in Linear Time
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CVPR
2007
IEEE
14 years 11 months ago
Sparse Kernels for Bayes Optimal Discriminant Analysis
Discriminant Analysis (DA) methods have demonstrated their utility in countless applications in computer vision and other areas of research ? especially in the C class classificat...
Aleix M. Martínez, Onur C. Hamsici
IEEEMM
2007
146views more  IEEEMM 2007»
13 years 9 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...
ICPR
2010
IEEE
14 years 15 hour ago
A Discriminative and Heteroscedastic Linear Feature Transformation for Multiclass Classification
This paper presents a novel discriminative feature transformation, named full-rank generalized likelihood ratio discriminant analysis (fGLRDA), on the grounds of the likelihood ra...
Hung-Shin Lee, Hsin-Min Wang, Berlin Chen
IJCNN
2006
IEEE
14 years 3 months ago
Classify Unexpected News Impacts to Stock Price by Incorporating Time Series Analysis into Support Vector Machine
— the paper discusses an approach of using traditional time series analysis, as domain knowledge, to help the data-preparation of support vector machine for classifying documents...
Ting Yu, Tony Jan, John K. Debenham, Simeon J. Sim...
ICML
2007
IEEE
14 years 10 months ago
Piecewise pseudolikelihood for efficient training of conditional random fields
Discriminative training of graphical models can be expensive if the variables have large cardinality, even if the graphical structure is tractable. In such cases, pseudolikelihood...
Charles A. Sutton, Andrew McCallum