Collecting large consistent data sets for real world software projects is problematic. Therefore, we explore how little data are required before the predictor performance plateaus...
We address the problem of efficiently learning Naive Bayes classifiers under classconditional classification noise (CCCN). Naive Bayes classifiers rely on the hypothesis that the ...
This paper presents a multimodal learning system that can ground spoken names of objects in their physical referents and learn to recognize those objects simultaneously from natur...
In this paper, a kernel-based SOM-face method is proposed to recognize expression variant faces under the situation of only one training image per person. Based on the localization...
We describe the process of converting plain text cultural heritage data to elements of a domain-specific knowledge base, using general machine learning techniques. First, digitise...