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 address the problem of efficiently learning Naive Bayes classifiers under classconditional classification noise (CCCN). Naive Bayes classifiers rely on the hypothesis that the ...
Kernel machines (e.g. SVM, KLDA) have shown state-ofthe-art performance in several visual classification tasks. The classification performance of kernel machines greatly depends o...
We report on the successful application of feature selection methods to a classification problem in molecular biology involving only 72 data points in a 7130 dimensional space. Ou...
Low overhead analysis of large distributed data sets is necessary for current data centers and for future sensor networks. In such systems, each node holds some data value, e.g., ...