Efficient estimation of tail probabilities involving heavy tailed random variables is amongst the most challenging problems in Monte-Carlo simulation. In the last few years, appli...
Abstract. Markov logic, as a highly expressive representation formalism that essentially combines the semantics of probabilistic graphical models with the full power of first-orde...
Dominik Jain, Bernhard Kirchlechner, Michael Beetz
This paper presents a grammar formalism in which constituent graphs are unions of a continuous surface tree and a discontinuous deep tree. The formalism has an object-oriented desi...
Constructing accurate classifier based on association rule is an important and challenging task in data mining. In this paper, a novel combination strategy based on rough sets (RST...
Existing work shows that classic decision trees have inherent deficiencies in obtaining a good probability-based ranking (e.g. AUC). This paper aims to improve the ranking perfor...