Cumulative restricted Boltzmann machines for ordinal matrix data analysis
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 ve...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Conference Paper |
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JMLR
2012
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| Subjects: | |
| Online Access: | http://jmlr.csail.mit.edu/proceedings/ http://hdl.handle.net/20.500.11937/4560 |
| _version_ | 1848744550416252928 |
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| author | Tran, Truyen Phung, D. Venkatesh, S. |
| author2 | C H Roi |
| author_facet | C H Roi Tran, Truyen Phung, D. Venkatesh, S. |
| author_sort | Tran, Truyen |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | 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 |
| first_indexed | 2025-11-14T06:03:15Z |
| format | Conference Paper |
| id | curtin-20.500.11937-4560 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T06:03:15Z |
| publishDate | 2012 |
| publisher | JMLR |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-45602023-02-02T07:57:36Z Cumulative restricted Boltzmann machines for ordinal matrix data analysis Tran, Truyen Phung, D. Venkatesh, S. C H Roi Wray Buntine ordinal analysis matrix data Cumulative restricted Boltzmann machine 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 2012 Conference Paper http://hdl.handle.net/20.500.11937/4560 http://jmlr.csail.mit.edu/proceedings/ JMLR fulltext |
| spellingShingle | ordinal analysis matrix data Cumulative restricted Boltzmann machine Tran, Truyen Phung, D. Venkatesh, S. Cumulative restricted Boltzmann machines for ordinal matrix data analysis |
| title | Cumulative restricted Boltzmann machines for ordinal matrix data analysis |
| title_full | Cumulative restricted Boltzmann machines for ordinal matrix data analysis |
| title_fullStr | Cumulative restricted Boltzmann machines for ordinal matrix data analysis |
| title_full_unstemmed | Cumulative restricted Boltzmann machines for ordinal matrix data analysis |
| title_short | Cumulative restricted Boltzmann machines for ordinal matrix data analysis |
| title_sort | cumulative restricted boltzmann machines for ordinal matrix data analysis |
| topic | ordinal analysis matrix data Cumulative restricted Boltzmann machine |
| url | http://jmlr.csail.mit.edu/proceedings/ http://hdl.handle.net/20.500.11937/4560 |