In the paper we show that diagnostic classes in cancer gene expression data sets, which most often include thousands of features (genes), may be effectively separated with simple ...
Gregor Leban, Minca Mramor, Ivan Bratko, Blaz Zupa...
Two of the most commonly used models in computational learning theory are the distribution-free model in which examples are chosen from a fixed but arbitrary distribution, and the ...
Abstract: Due the multiplicity of loci of control, a main issue distributed systems have to cope with lies in the uncertainty on the system state created by the adversaries that ar...
Abstract. Constraint Satisfaction has been widely used to model static combinatorial problems. However, many AI problems are dynamic and take place in a distributed environment, i....
Background: Advances in biotechnology and in high-throughput methods for gene analysis have contributed to an exponential increase in the number of scientific publications in thes...