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FLAIRS
2004
13 years 9 months ago
Case-Based Bayesian Network Classifiers
We propose a new approach for learning Bayesian classifiers from data. Although it relies on traditional Bayesian network (BN) learning algorithms, the effectiveness of our approa...
Eugene Santos, Ahmed Huessin
IJCNN
2008
IEEE
14 years 2 months ago
Hybrid learning architecture for unobtrusive infrared tracking support
—The system architecture presented in this paper is designed for helping an aged person to live longer independently in their own home by detecting unusual and potentially hazard...
K. K. Kiran Bhagat, Stefan Wermter, Kevin Burn
JMLR
2010
137views more  JMLR 2010»
13 years 2 months ago
Importance Sampling for Continuous Time Bayesian Networks
A continuous time Bayesian network (CTBN) uses a structured representation to describe a dynamic system with a finite number of states which evolves in continuous time. Exact infe...
Yu Fan, Jing Xu, Christian R. Shelton
JUCS
2008
160views more  JUCS 2008»
13 years 7 months ago
Automatic Construction of Fuzzy Rule Bases: a further Investigation into two Alternative Inductive Approaches
: The definition of the Fuzzy Rule Base is one of the most important and difficult tasks when designing Fuzzy Systems. This paper discusses the results of two different hybrid meth...
Marcos Evandro Cintra, Heloisa de Arruda Camargo, ...
GECCO
2006
Springer
167views Optimization» more  GECCO 2006»
13 years 11 months ago
Genomic computing networks learn complex POMDPs
A genomic computing network is a variant of a neural network for which a genome encodes all aspects, both structural and functional, of the network. The genome is evolved by a gen...
David J. Montana, Eric Van Wyk, Marshall Brinn, Jo...