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Cumulative restricted Boltzmann machines for ordinal matrix data analysis

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Open access
Authors
Tran, Truyen
Phung, D.
Venkatesh, S.
Date
2012
Type
Conference Paper

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Tran, Truyen and Phung, Dinh and Venkatesh, Svetha. 2012. Cumulative restricted Boltzmann machines for ordinal matrix data analysis, in Hoi, C.H. and Buntine, W. (ed), Proceedings of the 4th Asian conference on machine learning (ACML), Nov 4-6 2012, pp. 411-426. Singapore: JMLR.
Source Title
4th Asian Conference on Machine Learning
Source Conference
ACML12
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First published in the Journal of Machine Learning Research 2012.

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Abstract

Ordinal data is omnipresent in almost all multiuser-generated feedback - questionnaires,preferences etc. This paper investigates modelling of ordinal data with Gaussian restrictedBoltzmann machines (RBMs). In particular, we present the model architecture, learningand inference procedures for both vector-variate and matrix-variate ordinal data. We showthat our model is able to capture latent opinion prole of citizens around the world, andis competitive against state-of-art collaborative ltering techniques on large-scale publicdatasets. The model thus has the potential to extend application of RBMs to diversedomains such as recommendation systems, product reviews and expert assessments