Boosting methods are known not to usually overfit training data even as the size of the generated classifiers becomes large. Schapire et al. attempted to explain this phenomenon i...
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...
The classification of graph based objects is an important challenge from a knowledge discovery standpoint and has attracted considerable attention recently. In this paper, we pres...
H. D. K. Moonesinghe, Hamed Valizadegan, Samah Jam...
In region-based image annotation, keywords are usually associated with images instead of individual regions in the training data set. This poses a major challenge for any learning...
Active learning is a generic approach to accelerate training of classifiers in order to achieve a higher accuracy with a small number of training examples. In the past, simple ac...