The success of the Semantic Web crucially depends on the easy creation, integration and use of semantic data. For this purpose, we consider an integration scenario that defies co...
Sparse modeling is a powerful framework for data analysis and processing. Traditionally, encoding in this framework is performed by solving an 1-regularized linear regression prob...
Ensembles of learning machines have been formally and empirically shown to outperform (generalise better than) single predictors in many cases. Evidence suggests that ensembles ge...
We develop a new component analysis framework, the Noisy-Or Component Analyzer (NOCA), that targets high-dimensional binary data. NOCA is a probabilistic latent variable model tha...
This paper presents a market-enabling framework where users, content providers and network operators can interact in the seamless, transparent sale and delivery of a wide range of...