553 search results - page 53 / 111 » Bayesian network learning algorithms using structural restri... |
BMCBI
2010
14 years 9 months ago
2010
Background: Identifying candidate genes in genetic networks is important for understanding regulation and biological function. Large gene expression datasets contain relevant info...
DAGM
2007
Springer
15 years 1 months ago
2007
Springer
Abstract. In this article we present EANT2, a method that creates neural networks (NNs) by evolutionary reinforcement learning. The structure of NNs is developed using mutation ope...
NIPS
2008
14 years 11 months ago
2008
Learning graphical models with hidden variables can offer semantic insights to complex data and lead to salient structured predictors without relying on expensive, sometime unatta...
AAAI
1997
14 years 11 months ago
1997
In this paper, we propose a stochastic version of a general purpose functional programming language as a method of modeling stochastic processes. The language contains random choi...
CLEF
2009
Springer
14 years 10 months ago
2009
Springer
This paper investigates a novel approach to unsupervised morphology induction relying on community detection in networks. In a first step, morphological transformation rules are a...