Gaussian Mixture Model (GMM) is one of the most popular data clustering methods which can be viewed as a linear combination of different Gaussian components. In GMM, each cluster ...
In this paper we apply three different independent component analysis (ICA) methods, including spatial ICA (sICA), temporal ICA (tICA), and spatiotemporal ICA (stICA), to gene exp...
When developing systems based on COTS, components need to be adapted in most of the occasions to work under certain conditions which were not initially predicted by their develope...
Dependencies among system components are crucial to locating root errors in a distributed system. In this paper, we propose an approach to mine intercomponent dependencies from un...
In 2007 we introduced a general model of sparse random graphs with independence between the edges. The aim of this paper is to present an extension of this model in which the edge...