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JMLR
2002
89views more  JMLR 2002»
14 years 9 months ago
A Robust Minimax Approach to Classification
When constructing a classifier, the probability of correct classification of future data points should be maximized. We consider a binary classification problem where the mean and...
Gert R. G. Lanckriet, Laurent El Ghaoui, Chiranjib...
NIPS
2004
14 years 11 months ago
The Variational Ising Classifier (VIC) Algorithm for Coherently Contaminated Data
There has been substantial progress in the past decade in the development of object classifiers for images, for example of faces, humans and vehicles. Here we address the problem ...
Oliver M. C. Williams, Andrew Blake, Roberto Cipol...
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MVA
2007
110views Computer Vision» more  MVA 2007»
14 years 11 months ago
Improving Accuracy of 3-D Reconstruction by Classifying Correspondences
In this paper, we show that we can improve accuracies of 3-D reconstructions with uncalibrated stereo by classifying correspondences between two images. After obtaining initial co...
Yusuke Takanashi, Yohei Shibata, Yasushi Kanazawa
JMLR
2008
110views more  JMLR 2008»
14 years 9 months ago
Estimating the Confidence Interval for Prediction Errors of Support Vector Machine Classifiers
Support vector machine (SVM) is one of the most popular and promising classification algorithms. After a classification rule is constructed via the SVM, it is essential to evaluat...
Bo Jiang, Xuegong Zhang, Tianxi Cai
JMLR
2006
150views more  JMLR 2006»
14 years 9 months ago
Building Support Vector Machines with Reduced Classifier Complexity
Support vector machines (SVMs), though accurate, are not preferred in applications requiring great classification speed, due to the number of support vectors being large. To overc...
S. Sathiya Keerthi, Olivier Chapelle, Dennis DeCos...