We propose to solve the combinatorial problem of finding the highest scoring Bayesian network structure from data. This structure learning problem can be viewed as an inference pr...
Tommi Jaakkola, David Sontag, Amir Globerson, Mari...
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...
Background: Genes interact with each other as basic building blocks of life, forming a complicated network. The relationship between groups of genes with different functions can b...
Jong-Min Kim, Yoon-Sung Jung, Engin A. Sungur, Kap...
According to widely accepted guidelines for self-regulation, the capital requirements of a bank should relate to the level of risk with respect to three different categories. Amon...
Alessandro Antonucci, Alberto Piatti, Marco Zaffal...
The Student’s-t hidden Markov model (SHMM) has been recently proposed as a robust to outliers form of conventional continuous density hidden Markov models, trained by means of t...