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AI
2006
Springer
13 years 3 months ago
Controlled generation of hard and easy Bayesian networks: Impact on maximal clique size in tree clustering
This article presents and analyzes algorithms that systematically generate random Bayesian networks of varying difficulty levels, with respect to inference using tree clustering. ...
Ole J. Mengshoel, David C. Wilkins, Dan Roth
CORR
2010
Springer
132views Education» more  CORR 2010»
13 years 3 months ago
Bayesian Network Based XP Process Modelling
A Bayesian Network based mathematical model has been used for modelling Extreme Programming software development process. The model is capable of predicting the expected finish ti...
Mohamed Abouelela, Luigi Benedicenti
BMCBI
2008
166views more  BMCBI 2008»
13 years 3 months ago
Learning transcriptional regulatory networks from high throughput gene expression data using continuous three-way mutual informa
Background: Probability based statistical learning methods such as mutual information and Bayesian networks have emerged as a major category of tools for reverse engineering mecha...
Weijun Luo, Kurt D. Hankenson, Peter J. Woolf
BMCBI
2010
170views more  BMCBI 2010»
13 years 3 months ago
Analysis of lifestyle and metabolic predictors of visceral obesity with Bayesian Networks
Background: The aim of this study was to provide a framework for the analysis of visceral obesity and its determinants in women, where complex inter-relationships are observed amo...
Alex Aussem, André Tchernof, Sergio Rodrigu...
BMCBI
2010
147views more  BMCBI 2010»
13 years 3 months ago
Learning biological network using mutual information and conditional independence
Background: Biological networks offer us a new way to investigate the interactions among different components and address the biological system as a whole. In this paper, a revers...
Dong-Chul Kim, Xiaoyu Wang, Chin-Rang Yang, Jean G...
AI
2007
Springer
13 years 3 months ago
An application of formal argumentation: Fusing Bayesian networks in multi-agent systems
We consider a multi-agent system where each agent is equipped with a Bayesian network, and present an open framework for the agents to agree on a possible consensus network. The f...
Søren Holbech Nielsen, Simon Parsons
AI
2010
Springer
13 years 3 months ago
Understanding the scalability of Bayesian network inference using clique tree growth curves
Bayesian networks (BNs) are used to represent and ef ciently compute with multi-variate probability distributions in a wide range of disciplines. One of the main approaches to per...
Ole J. Mengshoel
HUC
2010
Springer
13 years 3 months ago
Bayesian recognition of motion related activities with inertial sensors
This work presents the design and evaluation of an activity recognition system for seven important motion related activities. The only sensor used is an Inertial Measurement Unit ...
Korbinian Frank, Maria Josefa Vera Nadales, Patric...
ECAI
2010
Springer
13 years 3 months ago
The Necessity of Bounded Treewidth for Efficient Inference in Bayesian Networks
Abstract. Algorithms for probabilistic inference in Bayesian networks are known to have running times that are worst-case exponential in the size of the network. For networks with ...
Johan Kwisthout, Hans L. Bodlaender, Linda C. van ...
GECCO
2008
Springer
135views Optimization» more  GECCO 2008»
13 years 4 months ago
iBOA: the incremental bayesian optimization algorithm
This paper proposes the incremental Bayesian optimization algorithm (iBOA), which modifies standard BOA by removing the population of solutions and using incremental updates of t...
Martin Pelikan, Kumara Sastry, David E. Goldberg