| Full text | |
| Author(s): |
de Faria, Francisco H. O. Vieira
[1]
;
Gusmao, Arthur Colombini
[1]
;
De Bona, Glauber
[1]
;
Maua, Denis Deratani
[2]
;
Cozman, Fabio Gagliardi
[1]
Total Authors: 5
|
| Affiliation: | [1] Univ Sao Paulo, Escola Politecn, Sao Paulo - Brazil
[2] Univ Sao Paulo, Inst Matemat & Estat, Sao Paulo - Brazil
Total Affiliations: 2
|
| Document type: | Journal article |
| Source: | INTERNATIONAL JOURNAL OF APPROXIMATE REASONING; v. 106, p. 32-50, MAR 2019. |
| Web of Science Citations: | 0 |
| Abstract | |
This paper introduces techniques that speed-up parameter and rule learning for acyclic probabilistic logic programs. We focus on maximum likelihood estimation of parameters, and show that significant improvements can be obtained by efficiently handling probabilistic rules. We then move to structure learning, where we learn sets of rules, by introducing an algorithm that greatly simplifies exact score-based learning. Experiments demonstrate that our methods can produce orders of magnitude speed-ups over the state-of-art in parameter and rule learning. (C) 2018 Elsevier Inc. All rights reserved. (AU) | |
| FAPESP's process: | 17/19007-6 - Inference and learning algorithms for probabilistic logic programming |
| Grantee: | Arthur Colombini Gusmão |
| Support Opportunities: | Scholarships in Brazil - Master |
| FAPESP's process: | 16/18841-0 - Inference and learning algorithms for probabilistic logic programming |
| Grantee: | Fabio Gagliardi Cozman |
| Support Opportunities: | Research Grants - Research Partnership for Technological Innovation - PITE |
| FAPESP's process: | 16/25928-4 - Probabilistic extensions for fragments of first-order logic |
| Grantee: | Glauber de Bona |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| 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 |
| FAPESP's process: | 15/21880-4 - PROVERBS -- PRobabilistic OVERconstrained Boolean Systems: reasoning tools and applications |
| Grantee: | Marcelo Finger |
| Support Opportunities: | Regular Research Grants |