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» Bio-medical entity extraction using support vector machines
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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
CVPR
2001
IEEE
14 years 9 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»
13 years 6 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
13 years 5 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»
13 years 7 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