In this paper we present a comparison of multiple cluster algorithms and their suitability for clustering text data. The clustering is based on similarities only, employing the Kol...
Tina Geweniger, Frank-Michael Schleif, Alexander H...
In kernel methods, an interesting recent development seeks to learn a good kernel from empirical data automatically. In this paper, by regarding the transductive learning of the k...
This paper describes and demonstrates the e ectiveness of several metrics for data level comparison of direct volume rendering (DVR) algorithms. The focus is not on speed ups from...
Background: The traditional (unweighted) k-means is one of the most popular clustering methods for analyzing gene expression data. However, it suffers three major shortcomings. It...
Abstract Data-parallel algorithms for R-trees, a common spatial data structure are presented, in the domain of planar line segment data e.g., Bureau of the Census TIGER Line les....