Sourek, Gustav, Manandhar, Suresh, Zelezny, Filip, Schockaert, Steven ORCID: https://orcid.org/0000-0002-9256-2881 and Kuzelka, Ondrej 2017. Learning predictive categories using lifted relational neural networks. Presented at: ILP 2016: International Conference on Inductive Logic Programming, London, UK, 4-6 September 2016. Published in: Cussens, James and Russo, Alexandra eds. Inductive Logic Programming. Lecture Notes in Computer Science. Lecture Notes in Computer Science , vol.10326 Cham: Springer, pp. 108-119. 10.1007/978-3-319-63342-8_9 |
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Official URL: http://dx.doi.org/10.1007/978-3-319-63342-8_9
Abstract
Lifted relational neural networks (LRNNs) are a flexible neural-symbolic framework based on the idea of lifted modelling. In this paper we show how LRNNs can be easily used to specify declaratively and solve learning problems in which latent categories of entities, properties and relations need to be jointly induced.
Item Type: | Conference or Workshop Item (Paper) |
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Date Type: | Publication |
Status: | Published |
Schools: | Computer Science & Informatics |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Publisher: | Springer |
ISBN: | 978-3-319-63342-8 |
ISSN: | 0302-9743 |
Date of First Compliant Deposit: | 11 January 2017 |
Last Modified: | 02 Nov 2022 10:01 |
URI: | https://orca.cardiff.ac.uk/id/eprint/97185 |
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