We propose a method for sequential Bayesian kernel regression. As is the case for the popular Relevance Vector Machine (RVM) [10, 11], the method automatically identifies the num...
The 2-class transduction problem, as formulated by Vapnik [1], involves finding a separating hyperplane for a labelled data set that is also maximally distant from a given set of...
Many problems in information processing involve some form of dimensionality reduction. In this paper, we introduce Locality Preserving Projections (LPP). These are linear projecti...
Several sophisticated methods are available for efficient rendering of out-of-core terrain data sets. For huge data sets the use of preprocessed tiles has proven to be more effici...
Roland Wahl, Manuel Massing, Patrick Degener, Mich...
In many application domains, data is collected and referenced by its geo-spatial location. Spatial data mining, or the discovery of interesting patterns in such databases, is an i...
Virtual and Augmented Reality allows a new way of result exploration of numerical simulations, its analysis and interpretation by immersing the user into the data sets and/or by k...
Using simulated data to develop and study diagnostic tools for data analysis is very beneficial. The user can gain insight about what happens when assumptions are violated since t...
We propose volume registration procedures based on spherical artificial markers presented in medical multimodal data sets (MRI and CT, especially). The procedures proposed are eit...
Several advanced techniques have been proposed for data clustering and many of them have been applied to gene expression data, with partial success. The high dimensionality and the...
Visualizing iso-surfaces of volumetric data sets is becoming increasingly important for many practical applications. One crucial task in iso-surface ray tracing is to find the cor...
Gerd Marmitt, Andreas Kleer, Ingo Wald, Heiko Frie...