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CDC
2010
IEEE
148views Control Systems» more  CDC 2010»
13 years 3 months ago
Distributed parameter estimation in networks
In this paper, we present a model of distributed parameter estimation in networks, where agents have access to partially informative measurements over time. Each agent faces a loca...
Kamiar Rahnama Rad, Alireza Tahbaz-Salehi
AI
2006
Springer
13 years 8 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
ICRA
2008
IEEE
150views Robotics» more  ICRA 2008»
14 years 3 months ago
Rigorously Bayesian range finder sensor model for dynamic environments
— This paper proposes and experimentally validates a Bayesian network model of a range finder adapted to dynamic environments. The modeling rigorously explains all model assumpt...
Tinne De Laet, Joris De Schutter, Herman Bruyninck...
GPEM
2008
98views more  GPEM 2008»
13 years 8 months ago
Sporadic model building for efficiency enhancement of the hierarchical BOA
Efficiency enhancement techniques--such as parallelization and hybridization--are among the most important ingredients of practical applications of genetic and evolutionary algori...
Martin Pelikan, Kumara Sastry, David E. Goldberg
IJAR
2010
97views more  IJAR 2010»
13 years 7 months ago
Parameter estimation and model selection for mixtures of truncated exponentials
Bayesian networks with mixtures of truncated exponentials (MTEs) support efficient inference algorithms and provide a flexible way of modeling hybrid domains (domains containing ...
Helge Langseth, Thomas D. Nielsen, Rafael Rum&iacu...