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...
Advanced analysis of data for extracting useful knowledge is the next natural step in the world of ubiquitous computing. So far, most of the ubiquitous systems process knowledge in...
This paper promotes the use of supervised machine learning in laboratory settings where chemists have a large number of samples to test for some property, and are interested in id...
Causal Probabilistic Networks (CPNs), (a.k.a. Bayesian Networks, or Belief Networks) are well-established representations in biomedical applications such as decision support system...
Constantin F. Aliferis, Ioannis Tsamardinos, Alexa...
Abstract. This paper describes an approach to detect hints on procurement fraud. It was developed within the context of a European Union project on fraud prevention. Procurement fr...