62 search results - page 1 / 13 » EM Algorithm for Symmetric Causal Independence Models |
ECML
2006
Springer
13 years 8 months ago
2006
Springer
Causal independence modelling is a well-known method both for reducing the size of probability tables and for explaining the underlying mechanisms in Bayesian networks. In this pap...
ICIP
2001
IEEE
14 years 5 months ago
2001
IEEE
The HMM (Hidden Markov Model) is a probabilistic model of the joint probability of a collection of random variables with both observations and states. The GMM (Gaussian Mixture Mo...
NIPS
1994
13 years 5 months ago
1994
Many real world learning problems are best characterized by an interaction of multiple independent causes or factors. Discovering such causal structure from the data is the focus ...
IJUFKS
2000
13 years 4 months ago
2000
Theefficiency of algorithmsfor probabilistic inference in Bayesian networks can be improvedby exploiting independenceof causal influence. Thefactorized representation of independe...
SGAI
2004
Springer
13 years 9 months ago
2004
Springer
The assessment of a probability distribution associated with a Bayesian network is a challenging task, even if its topology is sparse. Special probability distributions based on t...