273 search results - page 18 / 55 » Learning the Structure of Deep Sparse Graphical Models |
ICANN
2007
Springer
14 years 2 months ago
2007
Springer
Abstract. We present a novel approach to structure learning for graphical models. By using nonparametric estimates to model clique densities in decomposable models, both discrete a...
IJAR
2010
13 years 7 months ago
2010
Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by...
CORR
2012
Springer
12 years 4 months ago
2012
Springer
We present sparse topical coding (STC), a non-probabilistic formulation of topic models for discovering latent representations of large collections of data. Unlike probabilistic t...
ICML
2005
IEEE
14 years 9 months ago
2005
IEEE
Mappings to structured output spaces (strings, trees, partitions, etc.) are typically learned using extensions of classification algorithms to simple graphical structures (eg., li...
ICML
2005
IEEE
14 years 9 months ago
2005
IEEE
Learning the structure of graphical models is an important task, but one of considerable difficulty when latent variables are involved. Because conditional independences using hid...