We propose a new algorithm called SCD for learning the structure of a Bayesian network. The algorithm is a kind of constraintbased algorithm. By taking advantage of variable orderi...
Recently, relevance vector machines (RVM) have been fashioned from a sparse Bayesian learning (SBL) framework to perform supervised learning using a weight prior that encourages s...
We present two algorithms for learning large-scale gene regulatory networks from microarray data: a modified informationtheory-based Bayesian network algorithm and a modified asso...
Zan Huang, Jiexun Li, Hua Su, George S. Watts, Hsi...
Abstract. An artificial system that achieves human-level performance on opendomain tasks must have a huge amount of knowledge about the world. We argue that the most feasible way t...
This work proposes the exploration of student’s information through the use of Bayesian Networks. By using thisapproach we aim to model the uncertainty inherent to the studentâ€...