56 citations · 182 across the 17 of their papers we have counts for
11 papers · 1 filter
Learning Bounded Treewidth Bayesian Networks with Thousands of Variables
Mauro Scanagatta, Giorgio Corani, Cassio P. de Campos +1
We present a method for learning treewidth-bounded Bayesian networks from data sets containing thousands of variables. Bounding the treewidth of a Bayesian greatly reduces the comp…
Advances in Learning Bayesian Networks of Bounded Treewidth
Siqi Nie, Denis Deratani Maua, Cassio Polpo de Campos +1
This work presents novel algorithms for learning Bayesian network structures with bounded treewidth. Both exact and approximate methods are developed. The exact method combines mix…
On the Complexity of Strong and Epistemic Credal Networks
Denis D. Maua, Cassio Polpo de Campos, Alessio Benavoli +1
Credal networks are graph-based statistical models whose parameters take values in a set, instead of being sharply specified as in traditional statistical models (e.g., Bayesian ne…
Inference in Polytrees with Sets of Probabilities
Jose Carlos Ferreira da Rocha, Fabio Gagliardi Cozman, Cassio Polpo de Campos
Inferences in directed acyclic graphs associated with probability sets and probability intervals are NP-hard, even for polytrees. In this paper we focus on such inferences, and pro…
The Complexity of Approximately Solving Influence Diagrams
Denis D. Maua, Cassio Polpo de Campos, Marco Zaffalon
Influence diagrams allow for intuitive and yet precise description of complex situations involving decision making under uncertainty. Unfortunately, most of the problems described…
Propositional and Relational Bayesian Networks Associated with Imprecise and Qualitative Probabilistic Assesments
Fabio Gagliardi Cozman, Cassio Polpo de Campos, Jaime Ide +1
This paper investigates a representation language with flexibility inspired by probabilistic logic and compactness inspired by relational Bayesian networks. The goal is to handle p…