Sample selection bias is a common problem in many real world applications, where training data are obtained under realistic constraints that make them follow a different distribut...
Many approaches to object recognition are founded on probability theory, and can be broadly characterized as either generative or discriminative according to whether or not the di...
To address the problem of algorithm selection for the classification task, we equip a relational case base with new similarity measures that are able to cope with multirelational ...
We review some approaches to qualitative uncertainty and propose a new one based on the idea of Absolute Order of Magnitude. We show that our ideas can be useful for Knowledge Disc...
We regard answer extraction of Question Answering (QA) system as a classification problem, classifying answer candidate sentences into positive or negative. To confirm the feasibil...