84 search results - page 1 / 17 » Learning structurally consistent undirected probabilistic gr... |
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
In many real-world domains, undirected graphical models such as Markov random fields provide a more natural representation of the dependency structure than directed graphical mode...
ECML
2006
Springer
13 years 11 months ago
2006
Springer
Abstract. We propose a simple and efficient approach to building undirected probabilistic classification models (Markov networks) that extend na
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
There are well known algorithms for learning the structure of directed and undirected graphical models from data, but nearly all assume that the data consists of a single i.i.d. s...
AAAI
2007
13 years 10 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 ...
FTCGV
2011
12 years 11 months ago
2011
Powerful statistical models that can be learned efficiently from large amounts of data are currently revolutionizing computer vision. These models possess a rich internal structur...