This article presents and analyzes algorithms that systematically generate random Bayesian networks of varying difficulty levels, with respect to inference using tree clustering. ...
Classification is a key problem in machine learning/data mining. Algorithms for classification have the ability to predict the class of a new instance after having been trained on...
Jerffeson Teixeira de Souza, Stan Matwin, Nathalie...
Manual classification of free-text documents within a predefined hierarchy is highly time consuming. This is especially true for clinical guidelines, which are often indexed by mu...
Robert Moskovitch, Shiva Cohen-Kashi, Uzi Dror, If...
The formalism of probabilistic graphical models provides a unifying framework for capturing complex dependencies among random variables, and building large-scale multivariate stat...
The behavior of rational selfish agents has been classically studied in the framework of strategic games in which each player has a set of possible actions, players choose actions ...