84 search results - page 1 / 17 » Learning structurally consistent undirected probabilistic gr... |
ICML
2009
IEEE
14 years 5 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 8 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 5 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 7 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 8 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...