In recent years, there is a growing interest in learning Bayesian networks with continuous variables. Learning the structure of such networks is a computationally expensive proced...
We propose a cooperative-coevolution – Parisian trend – algorithm, IMPEA (Independence Model based Parisian EA), to the problem of Bayesian networks structure estimation. It i...
In this paper, we describe the program structure tree (PST), a hierarchical representation of program structure based on single entry single exit (SESE) regions of the control flo...
We propose two algorithms for grouping and summarizing association rules. The first algorithm recursively groups rules according to the structure of the rules and generates a tre...
The task of causal structure discovery from empirical data is a fundamental problem in many areas. Experimental data is crucial for accomplishing this task. However, experiments a...