273 search results - page 18 / 55 » Learning the Structure of Deep Sparse Graphical Models |
ICANN
2007
Springer
15 years 8 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...
121
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IJAR
2010
15 years 10 days 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...
126
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CORR
2012
Springer
13 years 9 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...
129
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ICML
2005
IEEE
16 years 2 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...
120
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ICML
2005
IEEE
16 years 2 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...