1340 search results - page 10 / 268 » Structure learning of Bayesian networks using constraints |
IPL
2008
13 years 6 months ago
2008
Bayesian Network structures with a maximum in-degree of k can be approximated with respect to a positive scoring metric up to an factor of 1/k. Key words: approximation algorithm,...
ICML
2007
IEEE
14 years 7 months ago
2007
IEEE
We propose a class of graphical models appropriate for structure prediction problems where the model structure is a function of the output structure. Incremental Sigmoid Belief Ne...
IJON
2008
13 years 6 months ago
2008
This paper proposed a kind of unsupervised learning neural network model, which has special structure and can realize an evaluation and classification of many groups by the compres...
NIPS
2008
13 years 8 months ago
2008
With the increased availability of data for complex domains, it is desirable to learn Bayesian network structures that are sufficiently expressive for generalization while at the ...
AUSAI
2006
Springer
13 years 10 months ago
2006
Springer
Abstract. We use a Markov Chain Monte Carlo (MCMC) MML algorithm to learn hybrid Bayesian networks from observational data. Hybrid networks represent local structure, using conditi...