Traditional classification involves building a classifier using labeled training examples from a set of predefined classes and then applying the classifier to classify test instan...
In this paper we propose a weakly supervised learning algorithm for appearance models based on the minimum description length (MDL) principle. From a set of training images or volu...
Georg Langs, Rene Donner, Philipp Peloschek, Horst...
Many real-world domains present the problem of imbalanced data sets, where examples of one classes significantly outnumber examples of other classes. This makes learning difficu...
Research is being done within the Computer Supported Collaborative Learning community to investigate how to apply the approach of Problem Oriented Project Pedagogy in distance lea...
We introduce an expandable Bayesian network (EBN) to handle the combination of diverse multiple homogeneous evidence sets. An EBN is an augmented Bayesian network which instantiat...