Answering queries in hybrid Bayesian networks using importance sampling
In this paper we propose an algorithm for answering queries in hybrid Bayesian networks where the underlying probability distribution is of class MTE (mixture of truncated exponentials). The algorithm is based on importance sampling simulation. We show how, like existing importance sampling algorith...
| Main Authors: | , , |
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| Format: | info:eu-repo/semantics/article |
| Language: | English |
| Published: |
2017
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10835/4895 https://doi.org/10.1016/j.dss.2012.03.007 |
| _version_ | 1789406282506043392 |
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| author | Fernández, Antonio Rumí, Rafael Salmerón Cerdán, Antonio |
| author_facet | Fernández, Antonio Rumí, Rafael Salmerón Cerdán, Antonio |
| author_sort | Fernández, Antonio |
| collection | DSpace |
| description | In this paper we propose an algorithm for answering queries in hybrid Bayesian networks where the underlying probability distribution is of class MTE (mixture of truncated exponentials). The algorithm is based on importance sampling simulation. We show how, like existing importance sampling algorithms for discrete networks, it is able to provide answers to multiple queries simultaneously using a single sample. The behaviour of the new algorithm is experimentally tested and compared with previous methods existing in the literature. |
| format | info:eu-repo/semantics/article |
| id | oai:repositorio.ual.es:10835-4895 |
| institution | Universidad de Cuenca |
| language | English |
| publishDate | 2017 |
| record_format | dspace |
| spelling | oai:repositorio.ual.es:10835-48952023-04-12T19:36:11Z Answering queries in hybrid Bayesian networks using importance sampling Fernández, Antonio Rumí, Rafael Salmerón Cerdán, Antonio Bayesian networks Probabilistic reasoning Importance sampling Mixtures of truncated exponentials In this paper we propose an algorithm for answering queries in hybrid Bayesian networks where the underlying probability distribution is of class MTE (mixture of truncated exponentials). The algorithm is based on importance sampling simulation. We show how, like existing importance sampling algorithms for discrete networks, it is able to provide answers to multiple queries simultaneously using a single sample. The behaviour of the new algorithm is experimentally tested and compared with previous methods existing in the literature. 2017-07-07T07:17:32Z 2017-07-07T07:17:32Z 2012 info:eu-repo/semantics/article http://hdl.handle.net/10835/4895 https://doi.org/10.1016/j.dss.2012.03.007 en Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess |
| spellingShingle | Bayesian networks Probabilistic reasoning Importance sampling Mixtures of truncated exponentials Fernández, Antonio Rumí, Rafael Salmerón Cerdán, Antonio Answering queries in hybrid Bayesian networks using importance sampling |
| title | Answering queries in hybrid Bayesian networks using importance sampling |
| title_full | Answering queries in hybrid Bayesian networks using importance sampling |
| title_fullStr | Answering queries in hybrid Bayesian networks using importance sampling |
| title_full_unstemmed | Answering queries in hybrid Bayesian networks using importance sampling |
| title_short | Answering queries in hybrid Bayesian networks using importance sampling |
| title_sort | answering queries in hybrid bayesian networks using importance sampling |
| topic | Bayesian networks Probabilistic reasoning Importance sampling Mixtures of truncated exponentials |
| url | http://hdl.handle.net/10835/4895 https://doi.org/10.1016/j.dss.2012.03.007 |
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