18 search results - page 1 / 4 » Learning Undirected Possibilistic Networks with Conditional ... |
FUZZIEEE
2007
IEEE
13 years 11 months ago
2007
IEEE
—Approaches based on conditional independence tests are among the most popular methods for learning graphical models from data. Due to the predominance of Bayesian networks in th...
SDM
2008
SIAM
13 years 6 months ago
2008
SIAM
In this paper we present the Dynamic Grow-Shrink Inference-based Markov network learning algorithm (abbreviated DGSIMN), which improves on GSIMN, the state-ofthe-art algorithm for...
ICASSP
2010
IEEE
13 years 5 months ago
2010
IEEE
In order to structure a gene network, a score-based approach is often used. A score-based approach, however, is problematic because by assuming a probability distribution, one is ...
UAI
2001
13 years 6 months ago
2001
In this paper we present a method of computing the posterior probability of conditional independence of two or more continuous variables from data, examined at several resolutions...
JMLR
2011
12 years 11 months ago
2011
We present a class of graphical models for directly representing the joint cumulative distribution function (CDF) of many random variables, called cumulative distribution networks...