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» Language networks: Their structure, function, and evolution
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UAI
2003
15 years 1 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
112
Voted
GECCO
2006
Springer
218views Optimization» more  GECCO 2006»
15 years 3 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»
14 years 6 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»
14 years 11 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
15 years 5 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...