3677 search results - page 376 / 736 » Is a probabilistic modeling |
183
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NIPS
2000
15 years 8 months ago
2000
A serious problem in learning probabilistic models is the presence of hidden variables. These variables are not observed, yet interact with several of the observed variables. As s...
170
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JMLR
2002
15 years 6 months ago
2002
Approximate Bayesian Gaussian process (GP) classification techniques are powerful nonparametric learning methods, similar in appearance and performance to support vector machines....
216
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ECAI
2010
Springer
15 years 4 months ago
2010
Springer
Conditional random fields (CRF) are widely used for predicting output variables that have some internal structure. Most of the CRF research has been done on structured classificati...
235
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ICFEM
2009
Springer
16 years 1 months ago
2009
Springer
Abstract. We study the problem of applying statistical methods for approximate model checking of probabilistic systems against properties encoded as PCTL formulas. Such approximate...
196
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IBERAMIA
2010
Springer
15 years 5 months ago
2010
Springer
We define a class of graphs that summarize in a compact visual way the interaction structure between binary multivariate characteristics. This allows studying the conditional depe...