-- Combination of multiple clusterings is an important task in the area of unsupervised learning. Inspired by the success of supervised bagging algorithms, we propose a resampling ...
Behrouz Minaei-Bidgoli, Alexander P. Topchy, Willi...
Complexity of post-genomic data and multiplicity of mining strategies are two limits to Knowledge Discovery in Databases (KDD) in life sciences. Because they provide a semantic fr...
The use of multiprocessor tasks (M-tasks) has been shown to be successful for mixed task and data parallel implementations of algorithms from scientific computing. The approach o...
Modern geographic databases can contain a large volume of data that need to be distributed to subscribed customers. The data can be modeled as a cube, where typical dimensions inc...
Background: Multivariate ordination methods are powerful tools for the exploration of complex data structures present in microarray data. These methods have several advantages com...
Florent Baty, Daniel Jaeger, Frank Preiswerk, Mart...