Power transformers' failures carry great costs to electric companies since they need resources to recover from them and to perform periodical maintenance. To avoid this probl...
We consider the semi-supervised learning problem, where a decision rule is to be learned from labeled and unlabeled data. In this framework, we motivate minimum entropy regulariza...
A model-based clustering method is proposed for clustering individuals on the basis of measurements taken over time. Data variability is taken into account through non-linear hier...
Automatic classification of documents is an important area of research with many applications in the fields of document searching, forensics and others. Methods to perform classif...
Many low-level vision algorithms assume a prior probability over images, and there has been great interest in trying to learn this prior from examples. Since images are very non G...