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JMLR
2006
169views more  JMLR 2006»
13 years 10 months ago
Bayesian Network Learning with Parameter Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
BMCBI
2008
154views more  BMCBI 2008»
13 years 10 months ago
Bayesian models and meta analysis for multiple tissue gene expression data following corticosteroid administration
Background: This paper addresses key biological problems and statistical issues in the analysis of large gene expression data sets that describe systemic temporal response cascade...
Yulan Liang, Arpad Kelemen
ICRA
2008
IEEE
150views Robotics» more  ICRA 2008»
14 years 4 months ago
A Bayesian approach to empirical local linearization for robotics
— Local linearizations are ubiquitous in the control of robotic systems. Analytical methods, if available, can be used to obtain the linearization, but in complex robotics system...
Jo-Anne Ting, Aaron D'Souza, Sethu Vijayakumar, St...
ISI
2006
Springer
13 years 10 months ago
An Embedded Bayesian Network Hidden Markov Model for Digital Forensics
In the paper we combine a Bayesian Network model for encoding forensic evidence during a given time interval with a Hidden Markov Model (EBN-HMM) for tracking and predicting the de...
Olivier Y. de Vel, Nianjun Liu, Terry Caelli, Tib&...
INFSOF
2007
139views more  INFSOF 2007»
13 years 9 months ago
Predicting software defects in varying development lifecycles using Bayesian nets
An important decision problem in many software projects is when to stop testing and release software for use. For many software products, time to market is critical and therefore ...
Norman E. Fenton, Martin Neil, William Marsh, Pete...