Graph-based methods for semi-supervised learning have recently been shown to be promising for combining labeled and unlabeled data in classification problems. However, inference f...
This paper discusses issues related to Bayesian network model learning for unbalanced binary classification tasks. In general, the primary focus of current research on Bayesian ne...
—One common approach to active learning is to iteratively train a single classifier by choosing data points based on its uncertainty, but it is nontrivial to design uncertainty ...
Recently there has been increasing interest in the problem of transfer learning, in which the typical assumption that training and testing data are drawn from identical distributi...
This paper presents the results of an investigation into the use of machine learning methods for the identification of narcotics from Raman spectra. The classification of spectr...
Tom Howley, Michael G. Madden, Marie-Louise O'Conn...