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Centre for Pattern Recognition and Data Analytics
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T. Tran, D.Q. Phung, and S. Venkatesh. Cumulative restricted Boltzmann machines for ordinal matrix data analysis. In Proceedings of 4th Asian Conference on Machine Learning, 2012.

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

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19th February 2015