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Deep relational machines
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Lodhi, Huma (2013) Deep relational machines. In: Hirose , Akira and Hou , Zeng-Guang and Kil, Rhee Man, (eds.) Neural Information Processing. Lecture Notes in Computer Science, Volume 8227 . Berlin Heidelberg: Springer, pp. 212-219. ISBN 9783642420412
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Official URL: http://dx.doi.org/10.1007/978-3-642-42042-9_27
Abstract
Deep learning methods that comprise a new class of learning algorithms give state-of-the-art performance. We propose a novel methodology to learn deep architectures and refer to it as a deep relational machine (DRM). A DRM learns the first layer of representation by inducing first order Horn clauses and the successive layers are generated by utilizing restricted Boltzmann machines. It is characterised by its ability to capture structural and relational information contained in data. To evaluate our approach, we apply it to challenging problems including protein fold recognition and detection of toxic and mutagenic compounds. The experimental results demonstrate that our technique substantially outperforms all other approaches in the study.
Item Type: | Book Item | ||||
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Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||
Series Name: | Lecture Notes in Computer Science | ||||
Publisher: | Springer | ||||
Place of Publication: | Berlin Heidelberg | ||||
ISBN: | 9783642420412 | ||||
ISSN: | 0302-9743 | ||||
Book Title: | Neural Information Processing | ||||
Editor: | Hirose , Akira and Hou , Zeng-Guang and Kil, Rhee Man | ||||
Official Date: | 2013 | ||||
Dates: |
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Volume: | Volume 8227 | ||||
Page Range: | pp. 212-219 | ||||
DOI: | 10.1007/978-3-642-42042-9_27 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Description: | |||||
Title of Event: | 20th International Conference, ICONIP 2013 | ||||
Type of Event: | Conference | ||||
Location of Event: | Daegu, Korea | ||||
Date(s) of Event: | 3-7 Nov 2013 |
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