As part of the efforts put in understanding the intricacies of the k-colorability problem, different distributions over k-colorable graphs were analyzed. While the problem is notor...
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
Abstract. The accurate extraction of scholarly reference information from scientific publications is essential for many useful applications like BIBTEX management systems or citati...
When performing concept description, models need to be evaluated both on accuracy and comprehensibility. A comprehensible concept description model should present the most importan...
This paper proposes a multiclassification algorithm using multilayer perceptron neural network models. It tries to boost two conflicting main objectives of multiclassifiers: a high...