This paper proposes a method for Bayesian networks that handles uncertainty and discretization of continuous variables when learning the networks from a database of cases. The dat...
The paper presents two experiments of unsupervised classification of Italian noun phrases. The goal of the experiments is to identify the most prominent contextual properties that...
In this paper two agglomerative learning algorithms based on new similarity measures defined for hyperbox fuzzy sets are proposed. They are presented in a context of clustering and...
Abstract. Activity inference based on object use has received considerable recent attention. Such inference requires statistical models that map activities to the objects used in p...
In this paper we present a scalable protocol for conducting periodic probes of network performance in a way that minimizes collisions between separate probes. The goal of the prot...
Richard Wolski, Benjamin Gaidioz, Bernard Touranch...