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» Language networks: Their structure, function, and evolution
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UAI
2003
13 years 9 months ago
Learning Continuous Time Bayesian Networks
Continuous time Bayesian networks (CTBN) describe structured stochastic processes with finitely many states that evolve over continuous time. A CTBN is a directed (possibly cycli...
Uri Nodelman, Christian R. Shelton, Daphne Koller
GECCO
2006
Springer
218views Optimization» more  GECCO 2006»
13 years 11 months ago
Genetic programming with primitive recursion
When Genetic Programming is used to evolve arithmetic functions it often operates by composing them from a fixed collection of elementary operators and applying them to parameters...
Stefan Kahrs
JMLR
2010
143views more  JMLR 2010»
13 years 2 months ago
Incremental Sigmoid Belief Networks for Grammar Learning
We propose a class of Bayesian networks appropriate for structured prediction problems where the Bayesian network's model structure is a function of the predicted output stru...
James Henderson, Ivan Titov
BMCBI
2010
178views more  BMCBI 2010»
13 years 7 months ago
Applications of a formal approach to decipher discrete genetic networks
Background: A growing demand for tools to assist the building and analysis of biological networks exists in systems biology. We argue that the use of a formal approach is relevant...
Fabien Corblin, Eric Fanchon, Laurent Trilling
SRDS
2007
IEEE
14 years 1 months ago
A Language-Based Approach for Improving the Robustness of Network Application Protocol Implementations
The secure and robust functioning of a network relies on the defect-free implementation of network applications. As network protocols have become increasingly complex, however, ha...
Laurent Burgy, Laurent Réveillère, J...