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» A Training Method with Small Computation for Classification
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ICML
2007
IEEE
14 years 6 months ago
Minimum reference set based feature selection for small sample classifications
We address feature selection problems for classification of small samples and high dimensionality. A practical example is microarray-based cancer classification problems, where sa...
Xue-wen Chen, Jong Cheol Jeong
ICIP
2002
IEEE
14 years 6 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
CVPR
2008
IEEE
13 years 11 months ago
Learning a geometry integrated image appearance manifold from a small training set
While low-dimensional image representations have been very popular in computer vision, they suffer from two limitations: (i) they require collecting a large and varied training se...
Yilei Xu, Amit K. Roy Chowdhury
EMNLP
2009
13 years 3 months ago
Re-Ranking Models Based-on Small Training Data for Spoken Language Understanding
The design of practical language applications by means of statistical approaches requires annotated data, which is one of the most critical constraint. This is particularly true f...
Marco Dinarelli, Alessandro Moschitti, Giuseppe Ri...
ICPR
2010
IEEE
13 years 3 months ago
One-Vs-All Training of Prototype Classifier for Pattern Classification and Retrieval
Prototype classifiers trained with multi-class classification objective are inferior in pattern retrieval and outlier rejection. To improve the binary classification (detection, v...
Cheng-Lin Liu