Identifying the Relevant Nodes Without Learning the Model
  We propose a method to identify all the nodes that are relevant to compute all the conditional probability distributions for a given set of nodes. Our method is simple, effcient, consistent, and does not require learning a Bayesian network first. Therefore, our method can be applied to high-dimensional databases, e.g. gene expression databases. 
Jose M. Pena, Roland Nilsson, Johan Bj\"orkegren, Jesper Tegn\'er
cs.LG cs.AI stat.ML