Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. In this pap...
The main aim of this paper is to develop a suitable regression analysis model for describing the relationship between the index efficiency and the parameters of the Rival Penaliz...
This paper presents a new method that uses orthogonalized features for time series clustering and classification. To cluster or classify time series data, either original data or...
A representation of the World Wide Web as a directed graph, with vertices representing web pages and edges representing hypertext links, underpins the algorithms used by web search...
Abstract. We present the Acyclic Bayesian Net Generator, a new approach to learn the structure of a Bayesian network using genetic algorithms. Due to the encoding mechanism, acycli...