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» Learning to learn with the informative vector machine
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BMCBI
2007
173views more  BMCBI 2007»
13 years 9 months ago
Recursive Cluster Elimination (RCE) for classification and feature selection from gene expression data
Background: Classification studies using gene expression datasets are usually based on small numbers of samples and tens of thousands of genes. The selection of those genes that a...
Malik Yousef, Segun Jung, Louise C. Showe, Michael...
BMCBI
2007
93views more  BMCBI 2007»
13 years 9 months ago
SVM-Fold: a tool for discriminative multi-class protein fold and superfamily recognition
Background: Predicting a protein’s structural class from its amino acid sequence is a fundamental problem in computational biology. Much recent work has focused on developing ne...
Iain Melvin, Eugene Ie, Rui Kuang, Jason Weston, W...
IJDAR
2010
110views more  IJDAR 2010»
13 years 7 months ago
Locating and parsing bibliographic references in HTML medical articles
The set of references that typically appear toward the end of journal articles is sometimes, though not always, a field in bibliographic (citation) databases. But even if referenc...
Jie Zou, Daniel X. Le, George R. Thoma
ICWSM
2009
13 years 6 months ago
Targeting Sentiment Expressions through Supervised Ranking of Linguistic Configurations
User generated content is extremely valuable for mining market intelligence because it is unsolicited. We study the problem of analyzing users' sentiment and opinion in their...
Jason S. Kessler, Nicolas Nicolov
ICASSP
2011
IEEE
13 years 27 days ago
Online Kernel SVM for real-time fMRI brain state prediction
The Support Vector Machine (SVM) methodology is an effective, supervised, machine learning method that gives stateof-the-art performance for brain state classification from funct...
Yongxin Taylor Xi, Hao Xu, Ray Lee, Peter J. Ramad...