136 search results - page 2 / 28 » Structure Inference of Bayesian Networks from Data: A New Ap... |
AIIA
2003
Springer
14 years 22 days ago
2003
Springer
A bayesian network is an appropriate tool for working with uncertainty and probability, that are typical of real-life applications. In literature we find different approaches for b...
CIARP
2009
Springer
14 years 2 months ago
2009
Springer
Abstract. An important problem in the bioinformatics field is to understand how genes are regulated and interact through gene networks. This knowledge can be helpful for many appl...
CSB
2004
IEEE
13 years 11 months ago
2004
IEEE
Clustering is a common methodology for analyzing the gene expression data. In this paper, we present a new clustering algorithm from an information-theoretic point of view. First,...
ICPR
2008
IEEE
14 years 1 months ago
2008
IEEE
This paper describes a new approach to unify constraints on parameters with training data to perform parameter estimation in Bayesian networks of known structure. The method is ge...
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
We propose Laplace max-margin Markov networks (LapM3 N), and a general class of Bayesian M3 N (BM3 N) of which the LapM3 N is a special case with sparse structural bias, for robus...