Learning Bayesian network structure from large-scale data sets, without any expertspecified ordering of variables, remains a difficult problem. We propose systematic improvements ...
In this paper, we address the correct refinement of abstract architectural models into more platformspecific representations. We consider the challenging case of dynamic architect...
Different types of two- and three-dimensional representations of a finite metric space are studied that focus on the accurate representation of the linear order among the distance...
This paper presents a user recommendation system that recommends to a user new friends having similar interests. We automatically discover users’ interests using Latent Dirichle...
This paper proposes a novel constructive learning algorithm for a competitive neural network. The proposed algorithm is developed by taking ideas from the immune system and demons...
Helder Knidel, Leandro Nunes de Castro, Fernando J...