The task of eliciting all probabilities required for a Bayesian network can be supported by first acquiring qualitative constraints on the numerical quantities to be obtained. Buil...
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
The problem of image segmentation using constraint satisfaction neural networks (CSNN) has been considered. Several variations of the CSNN theme have been advanced to improve its ...
Abstract. This paper demonstrates and exploits some interesting frequency-domain properties of nonstationary signals. Considering these properties, two new methods for blind separa...
Abstract. We summarize and reorganize some of the last decade's research on real-time extensions of temporal logic. Our main focus is on tableau constructions for model checki...