Abstract— Making inferences and choosing appropriate responses based on incomplete, uncertainty and noisy data is challenging in financial settings particularly in bankruptcy de...
In this paper, a new symmetry-based genetic clustering algorithm is proposed which automatically evolves the number of clusters as well as the proper partitioning from a data set. ...
Self-Organizing Maps (SOM) are very powerful tools for data mining, in particular for visualizing the distribution of the data in very highdimensional data sets. Moreover, the 2D m...
In this paper we present a meeting state recognizer based on a combination of multi-modal sensor data in a smart room. Our approach is based on the training of a statistical model ...
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...