In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Many techniques for association rule mining and feature selection require a suitable metric to capture the dependencies among variables in a data set. For example, metrics such as...
Modern scientific applications consume massive volumes of data produced by computer simulations. Such applications require new data management capabilities in order to scale to te...
This paper introduces LDA-G, a scalable Bayesian approach to finding latent group structures in large real-world graph data. Existing Bayesian approaches for group discovery (suc...
Abstract: The emerging penetration of IT architectures with XML leads to increasing XML data volumes. Available tools often fail in realizing scalable XML processing for large XML ...