Clustering Stability methods are a family of widely used model selection techniques applied in data clustering. Their unifying theme is that an appropriate model should result in ...
The inference of evolutionary trees using approaches which attempt to solve the maximum parsimony (MP) and maximum likelihood (ML) optimization problems is a standard part of much...
In this paper we examine a novel addition to the known methods for learning Bayesian networks from data that improves the quality of the learned networks. Our approach explicitly ...
We have previously proposed a new technique for the communication-free adaptive refinement of tetrahedral meshes that works for all configurations. Implementations of the scheme mu...
Contemporary embedded systems quite often employ extremely complicated software consisting of a number of interrelated components, and this has made object-oriented design methodo...