68 search results - page 2 / 14 » Learning Latent Tree Graphical Models |
AAAI
2011
12 years 5 months ago
2011
Important ecological phenomena are often observed indirectly. Consequently, probabilistic latent variable models provide an important tool, because they can include explicit model...
AAAI
2008
13 years 8 months ago
2008
We propose a novel method for approximate inference in Bayesian networks (BNs). The idea is to sample data from a BN, learn a latent tree model (LTM) from the data offline, and wh...
PKDD
2009
Springer
14 years 10 days ago
2009
Springer
Abstract. We propose a learning approach for integrating formal knowledge into statistical inference by exploiting ontologies as a semantically rich and fully formal representation...
ICML
2007
IEEE
14 years 6 months ago
2007
IEEE
The Gaussian process latent variable model (GP-LVM) is a powerful approach for probabilistic modelling of high dimensional data through dimensional reduction. In this paper we ext...
ICML
2010
IEEE
13 years 6 months ago
2010
IEEE
Maximum a posteriori (MAP) inference in graphical models requires that we maximize the sum of two terms: a data-dependent term, encoding the conditional likelihood of a certain la...