Abstract
The assessment of a probability distribution that is associated with a Bayesian network is a challenging task, even if its topology is sparse. Special probability distributions, based on the notion of causal independence, have therefore been proposed, as these allow defining a probability distribution in terms of Boolean combinations of local distributions. In Bayesian networks which need to model a large number of interactions among causal mechanisms even this approach becomes infeasible. We investigate the use of equivalence classes of binomial distributions as a means to define such very large Bayesian networks.
| Original language | English |
|---|---|
| Title of host publication | ECAI 2004 - |
| Subtitle of host publication | Proceedings of the 16th European Conference on Artificial Intelligence, including Prestigious Applications of Intelligent Systems (PAIS 2004) |
| Editors | Ramon Lopez de Mantaras, Lorenza Saitta |
| Publisher | IOS |
| Pages | 1037-1038 |
| Number of pages | 2 |
| ISBN (Electronic) | 9781586034528 |
| Publication status | Published - 2004 |
| Externally published | Yes |
| Event | 16th European Conference on Artificial Intelligence, ECAI 2004 - Valencia, Spain Duration: 22 Aug 2004 → 27 Aug 2004 Conference number: 16 |
Publication series
| Name | Frontiers in Artificial Intelligence and Applications |
|---|---|
| Publisher | IOS Press |
| Volume | 110 |
| ISSN (Print) | 0922-6389 |
| ISSN (Electronic) | 1879-8314 |
Conference
| Conference | 16th European Conference on Artificial Intelligence, ECAI 2004 |
|---|---|
| Abbreviated title | ECAI |
| Country/Territory | Spain |
| City | Valencia |
| Period | 22/08/04 → 27/08/04 |