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PR
2010
186views more  PR 2010»
14 years 10 months ago
Feature extraction by learning Lorentzian metric tensor and its extensions
We develop a supervised dimensionality reduction method, called Lorentzian Discriminant Projection (LDP), for feature extraction and classification. Our method represents the str...
Risheng Liu, Zhouchen Lin, Zhixun Su, Kewei Tang
NIPS
2008
15 years 1 months ago
Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning
For supervised and unsupervised learning, positive definite kernels allow to use large and potentially infinite dimensional feature spaces with a computational cost that only depe...
Francis Bach
100
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BMCBI
2006
142views more  BMCBI 2006»
14 years 11 months ago
Improving the Performance of SVM-RFE to Select Genes in Microarray Data
Background: Recursive Feature Elimination is a common and well-studied method for reducing the number of attributes used for further analysis or development of prediction models. ...
Yuanyuan Ding, Dawn Wilkins
DMIN
2006
114views Data Mining» more  DMIN 2006»
15 years 1 months ago
Towards Using Fewer Features for Text Classification
Abstract-- Text classification or categorization is a conventional classification problem applied to the text domain. In the cases when statistical classification methods are used,...
Yuan Yuan, Tianyang Gu
PAMI
2006
132views more  PAMI 2006»
14 years 11 months ago
Capitalize on Dimensionality Increasing Techniques for Improving Face Recognition Grand Challenge Performance
This paper presents a novel pattern recognition framework by capitalizing on dimensionality increasing techniques. In particular, the framework integrates Gabor image representatio...
Chengjun Liu