We propose a novel approach that reduces cost-sensitive classification to one-sided regression. The approach stores the cost information in the regression labels and encodes the m...
Many traditional methods for shape classification involve
establishing point correspondences between shapes to
produce matching scores, which are in turn used as similarity
meas...
A novel method to improve the generalization performance of the Minimum Classification Error (MCE) / Generalized Probabilistic Descent (GPD) learning is proposed. The MCE/GPD learn...
We compare the practical performance of several recently proposed algorithms for active learning in the online classification setting. We consider two active learning algorithms (...
We address the problem of efficiently learning Naive Bayes classifiers under classconditional classification noise (CCCN). Naive Bayes classifiers rely on the hypothesis that the ...