1450 search results - page 2 / 290 » Complexity of Inference in Graphical Models |
JMLR
2010
13 years 1 months ago
2010
It is probably fair to say that exact inference in graphical models is considered a solved problem, at least regarding its computational complexity: it is exponential in the treew...
UAI
2008
13 years 8 months ago
2008
The paper introduces a generalization for known probabilistic models such as log-linear and graphical models, called here multiplicative models. These models, that express probabi...
CVPR
2011
IEEE
13 years 3 months ago
2011
IEEE
Nearly every structured prediction problem in computer vision requires approximate inference due to large and complex dependencies among output labels. While graphical models prov...
JMLR
2010
13 years 1 months ago
2010
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
JMLR
2010
13 years 1 months ago
2010
We introduce a nonparametric representation for graphical model on trees which expresses marginals as Hilbert space embeddings and conditionals as embedding operators. This formul...