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ICML
2006
IEEE
14 years 8 months ago
The support vector decomposition machine
In machine learning problems with tens of thousands of features and only dozens or hundreds of independent training examples, dimensionality reduction is essential for good learni...
Francisco Pereira, Geoffrey J. Gordon
ICML
2004
IEEE
14 years 8 months ago
Support vector machine learning for interdependent and structured output spaces
Learning general functional dependencies is one of the main goals in machine learning. Recent progress in kernel-based methods has focused on designing flexible and powerful input...
Ioannis Tsochantaridis, Thomas Hofmann, Thorsten J...
CICLING
2010
Springer
13 years 2 months ago
An Empirical Study on the Feature's Type Effect on the Automatic Classification of Arabic Documents
The Arabic language is a highly flexional and morphologically very rich language. It presents serious challenges to the automatic classification of documents, one of which is deter...
Saeed Raheel, Joseph Dichy
PRL
2006
79views more  PRL 2006»
13 years 7 months ago
Multi-class feature selection for texture classification
In this paper, a multi-class feature selection scheme based on recursive feature elimination (RFE) is proposed for texture classifications. The feature selection scheme is perform...
Xue-wen Chen, Xiang-Yan Zeng, Deborah van Alphen
EMNLP
2009
13 years 5 months ago
Reverse Engineering of Tree Kernel Feature Spaces
We present a framework to extract the most important features (tree fragments) from a Tree Kernel (TK) space according to their importance in the target kernelbased machine, e.g. ...
Daniele Pighin, Alessandro Moschitti