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» Bio-medical entity extraction using support vector machines
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EMNLP
2009
14 years 9 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
CVPR
2001
IEEE
16 years 1 months ago
A New 3-D Pattern Recognition Technique With Application to Computer Aided Colonoscopy
To utilize CT or MRI images for computer aided diagnosis applications, robust features that represent 3-D image data need to be constructed and subsequently used by a classificati...
Salih Burak Göktürk, Carlo Tomasi
IJDAR
2010
110views more  IJDAR 2010»
14 years 10 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
ICMLA
2009
14 years 9 months ago
Feature Extraction and Classification of EEG Signals for Rapid P300 Mind Spelling
The Mind Speller is a Brain-Computer Interface which enables subjects to spell text on a computer screen by detecting P300 Event-Related Potentials in their electroencephalograms....
Adrien Combaz, Nikolay V. Manyakov, Nikolay Chumer...
TKDD
2008
113views more  TKDD 2008»
14 years 11 months ago
Privacy-preserving classification of vertically partitioned data via random kernels
We propose a novel privacy-preserving support vector machine (SVM) classifier for a data matrix A whose input feature columns are divided into groups belonging to different entiti...
Olvi L. Mangasarian, Edward W. Wild, Glenn Fung