| Full text | |
| Author(s): |
Cozman, Fabio Gagliardi
;
Maua, Denis Deratani
Total Authors: 2
|
| Document type: | Journal article |
| Source: | INTERNATIONAL JOURNAL OF APPROXIMATE REASONING; v. 83, p. 298-319, APR 2017. |
| Web of Science Citations: | 0 |
| Abstract | |
credal network associates a directed acyclic graph with a collection of sets of probability measures. Usually these probability measures are specified by tables containing probability values. Here we examine the complexity of inference in credal networks when probability measures are specified through formal languages. We focus on logical languages based on propositional logic and on the function-free fragment of first-order logic. We show that sub-Boolean and relational logics lead to interesting complexity results. In short, we explore the relationship between specification language and computational complexity in credal networks. (C) 2016 Elsevier Inc. All rights reserved. (AU) | |
| FAPESP's process: | 16/01055-1 - Learning of Tractable Probabilistic Models with Application to Multilabel Classification |
| Grantee: | Denis Deratani Mauá |
| Support Opportunities: | Regular Research Grants |