We present sparse topical coding (STC), a non-probabilistic formulation of topic models for discovering latent representations of large collections of data. Unlike probabilistic t...
The provenance of data has recently been recognized as central to the trust one places in data. It is also important to annotation, to data integration and to probabilistic databa...
Abstract. We present an exploratory method for simultaneous parcellation of multisubject fMRI data into functionally coherent areas. The method is based on a solely functional repr...
This paper investigates a new approach for training discriminant classifiers when only a small set of labeled data is available together with a large set of unlabeled data. This a...
: Utility companies worldwide are facing a multitude of new challenges, which can not be met with the historically grown, monolithic IT systems currently in use. Service oriented a...