1340 search results - page 40 / 268 » Structure learning of Bayesian networks using constraints |
JETAI
1998
14 years 11 months ago
1998
Graphical structures such as Bayesian networks or Markov networks are very useful tools for representing irrelevance or independency relationships, and they may be used to e cientl...
109
click to vote
IJCAI
2007
15 years 1 months ago
2007
Compiling Bayesian networks has proven an effective approach for inference that can utilize both global and local network structure. In this paper, we define a new method of comp...
118
click to vote
CORR
2011
Springer
14 years 6 months ago
2011
Springer
We consider a class of learning problems regularized by a structured sparsity-inducing norm defined as the sum of 2- or ∞-norms over groups of variables. Whereas much effort ha...
ICML
2005
IEEE
16 years 17 days ago
2005
IEEE
In this paper, we propose a probabilistic kernel approach to preference learning based on Gaussian processes. A new likelihood function is proposed to capture the preference relat...
UAI
2004
15 years 1 months ago
2004
Ancestral graph models, introduced by Richardson and Spirtes (2002), generalize both Markov random fields and Bayesian networks to a class of graphs with a global Markov property ...