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» Discriminative Direction for Kernel Classifiers
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NIPS
2001
13 years 11 months ago
Minimax Probability Machine
When constructing a classifier, the probability of correct classification of future data points should be maximized. In the current paper this desideratum is translated in a very ...
Gert R. G. Lanckriet, Laurent El Ghaoui, Chiranjib...
BMCBI
2006
173views more  BMCBI 2006»
13 years 10 months ago
Kernel-based distance metric learning for microarray data classification
Background: The most fundamental task using gene expression data in clinical oncology is to classify tissue samples according to their gene expression levels. Compared with tradit...
Huilin Xiong, Xue-wen Chen
CVPR
2004
IEEE
14 years 12 months ago
Improving Object Classification in Far-Field Video
Object classification in far-field video sequences is a challenging problem because of low resolution imagery and projective image distortion. Most existing far-field classificati...
Biswajit Bose, W. Eric L. Grimson
IJON
2006
117views more  IJON 2006»
13 years 9 months ago
EEG classification using generative independent component analysis
We present an application of Independent Component Analysis (ICA) to the discrimination of mental tasks for EEG-based Brain Computer Interface systems. ICA is most commonly used w...
Silvia Chiappa, David Barber
CSL
2006
Springer
13 years 9 months ago
Support vector machines for speaker and language recognition
Support vector machines (SVMs) have proven to be a powerful technique for pattern classification. SVMs map inputs into a high dimensional space and then separate classes with a hy...
William M. Campbell, Joseph P. Campbell, Douglas A...