Many clustering algorithms fail when dealing with high dimensional data. Principal component analysis (PCA) is a popular dimensionality reduction algorithm. However, it assumes a ...
Abstract. We analyze special random network models – so-called thickened trees – which are constructed by random trees where the nodes are replaced by local clusters. These obj...
Michael Drmota, Bernhard Gittenberger, Reinhard Ku...
Since the advent of electronic computing, the processors’ clock speed has risen tremendously. Now that energy efficiency requirements have stopped that trend, the number of proc...
This work introduces distance-based criteria for segmentation of object trajectories. Segmentation leads to simplification of the original objects into smaller, less complex primi...
: This paper describes a rather novel method for the supervised training of regression systems that can be an alternative to feedforward Artificial Neural Networks (ANNs) trained w...
Mark J. Embrechts, Dirk Devogelaere, Marcel Rijcka...