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» Discriminative Direction for Kernel Classifiers
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NIPS
2001
15 years 1 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»
14 years 11 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
16 years 1 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»
14 years 11 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
14 years 11 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...