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TCBB
2010
176views more  TCBB 2010»
13 years 6 months ago
Feature Selection for Gene Expression Using Model-Based Entropy
—Gene expression data usually contain a large number of genes, but a small number of samples. Feature selection for gene expression data aims at finding a set of genes that best...
Shenghuo Zhu, Dingding Wang, Kai Yu, Tao Li, Yihon...
ICML
2007
IEEE
14 years 8 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
EACL
2009
ACL Anthology
14 years 8 months ago
Re-Ranking Models for Spoken Language Understanding
Spoken Language Understanding aims at mapping a natural language spoken sentence into a semantic representation. In the last decade two main approaches have been pursued: generati...
Marco Dinarelli, Alessandro Moschitti, Giuseppe Ri...
ICIP
2005
IEEE
14 years 9 months ago
Robust facial expression recognition using local binary patterns
A novel low-computation discriminative feature space is introduced for facial expression recognition capable of robust performance over a rang of image resolutions. Our approach i...
Caifeng Shan, Shaogang Gong, Peter W. McOwan
EMO
2009
Springer
147views Optimization» more  EMO 2009»
14 years 2 months ago
Application of MOGA Search Strategy to SVM Training Data Selection
When training Support Vector Machine (SVM), selection of a training data set becomes an important issue, since the problem of overfitting exists with a large number of training da...
Tomoyuki Hiroyasu, Masashi Nishioka, Mitsunori Mik...