We propose the combination of two recently introduced methods for the interactive visual data mining of large collections of data. Both, Hyperbolic Multi-Dimensional Scaling (HMDS...
Landmark multidimensional scaling (LMDS) uses a subset of data (landmark points) to solve classical MDS, where the scalability is increased but the approximation is noise-sensitiv...
Monitoring and correlation of streaming data from multiple sources is becoming increasingly important in many application areas. Example applications include automated commodities...
Object space (OS) parallelization of an efficient direct volume rendering algorithm for unstructured grids on distributed-memory architectures is investigated. The adaptive OS de...
In the area of Grid computing, there is a growing need to process large amounts of data. To support this trend, we need to develop efficient parallel storage systems that can prov...