273 search results - page 5 / 55 » Learning the Structure of Deep Sparse Graphical Models |
122
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CORR
2012
Springer
13 years 7 months ago
2012
Springer
The key limiting factor in graphical model inference and learning is the complexity of the partition function. We thus ask the question: what are the most general conditions under...
ISNN
2007
Springer
15 years 5 months ago
2007
Springer
This paper investigates a mechanism for reliable generation of sparse code in a sparsely connected, hierarchical, learning memory. Activity reduction is accomplished with local com...
CORR
2010
Springer
14 years 11 months ago
2010
Springer
In this paper we propose an approximated structured prediction framework for large scale graphical models and derive message-passing algorithms for learning their parameters effic...
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AAAI
2007
15 years 2 months ago
2007
Sparsity-promoting L1-regularization has recently been succesfully used to learn the structure of undirected graphical models. In this paper, we apply this technique to learn the ...
MICCAI
1998
Springer
15 years 3 months ago
1998
Springer
We propose a new way of embedding shape distributions in a topological deformable template. These distributions rely on global shape descriptors corresponding to the 3D moment inva...