Browse wiki
From Semantic Portal Wiki
| An empirical analysis of likelihood-weighting simulation on a large, multiply-connected belief network |
| Abstract | We analyzed the convergence properties of … We analyzed the convergence properties of likelihood-weighting algorithms on a two-level, multiply connected, belief-network representation of the QMR knowledge base of internal medicine. Specifically, on two difficult diagnostic cases, we examined the effects of Markov blanket scoring, importance sampling, and self-importance sampling, demonstrating that the simulation on our model requires the Markov blanket scoring and self-importance sampling to converge well. self-importance sampling to converge well. |
|---|---|
| Author | Michael Shwe +, Gregory F. Cooper + |
| Bibtype | techreport + |
| Institution | Knowledge Systems, AI Laboratory + |
| Key | KSL-90-23 + |
| Modification dateThis property is a special property in this wiki. | 1 May 2009 14:05:44 + |
| Number | KSL-90-23 + |
| Tag | Computer science + |
| Title | An Empirical Analysis of Likelihood-Weighting Simulation on a Large, Multiply-Connected Belief Network + |
| Tr id | KSL-90-23 + |
| Year | 1991 + |
| Categories | Technical Report, Publication, KSL Technical Report |
| hide properties that link here |
| No properties link to this page. |
