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» Making inferences with small numbers of training sets
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82
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ICPR
2006
IEEE
16 years 26 days ago
Linear model combining by optimizing the Area under the ROC curve
In some classification problems, like the detection of illnesses in patients, classes are very unbalanced and the misclassification costs for different classes vary significantly....
David M. J. Tax, Robert P. W. Duin
FGR
2008
IEEE
304views Biometrics» more  FGR 2008»
15 years 6 months ago
Recovering 3D facial shape via coupled 2D/3D space learning
This paper presents a method for recovering 3D facial shape from single image via learning the relationship between the 2D intensity images and the 3D facial shapes. With a couple...
Annan Li, Shiguang Shan, Xilin Chen, Xiujuan Chai,...
SDM
2009
SIAM
175views Data Mining» more  SDM 2009»
15 years 9 months ago
Low-Entropy Set Selection.
Most pattern discovery algorithms easily generate very large numbers of patterns, making the results impossible to understand and hard to use. Recently, the problem of instead sel...
Hannes Heikinheimo, Jilles Vreeken, Arno Siebes, H...
ISBI
2008
IEEE
16 years 14 days ago
Controlling the error in FMRI: Hypothesis testing or set estimation?
This paper describes a new methodology and associated theoretical analysis for rapid and accurate extraction of activation regions from functional MRI data. Most fMRI data analysi...
Aarti Singh, Rebecca Willett, Robert Nowak, Zachar...
92
Voted
LREC
2010
209views Education» more  LREC 2010»
15 years 1 months ago
Lingua-Align: An Experimental Toolbox for Automatic Tree-to-Tree Alignment
In this paper we present an experimental toolbox for automatic tree-to-tree alignment based on local classification and alignment inference. The aligner implements a recurrent arc...
Jörg Tiedemann