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» On learning algorithm selection for classification
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ICML
2009
IEEE
14 years 9 months ago
Partially supervised feature selection with regularized linear models
This paper addresses feature selection techniques for classification of high dimensional data, such as those produced by microarray experiments. Some prior knowledge may be availa...
Thibault Helleputte, Pierre Dupont
CVPR
2010
IEEE
13 years 6 months ago
Visual classification with multi-task joint sparse representation
We address the problem of computing joint sparse representation of visual signal across multiple kernel-based representations. Such a problem arises naturally in supervised visual...
Xiaotong Yuan, Shuicheng Yan
NAACL
2010
13 years 6 months ago
Improving Semantic Role Classification with Selectional Preferences
This work incorporates Selectional Preferences (SP) into a Semantic Role (SR) Classification system. We learn separate selectional preferences for noun phrases and prepositional p...
Beñat Zapirain, Eneko Agirre, Lluís ...
CSDA
2008
126views more  CSDA 2008»
13 years 8 months ago
A new genetic algorithm in proteomics: Feature selection for SELDI-TOF data
Mass spectrometry from clinical specimens is used in order to identify biomarkers in a diagnosis. Thus, a reliable method for both feature selection and classification is required...
Christelle Reynès, Robert Sabatier, Nicolas...
ICML
2005
IEEE
14 years 9 months ago
Learning hierarchical multi-category text classification models
We present a kernel-based algorithm for hierarchical text classification where the documents are allowed to belong to more than one category at a time. The classification model is...
Craig Saunders, John Shawe-Taylor, Juho Rousu, S&a...