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PPSN
2004
Springer
15 years 10 months ago
Learning Probabilistic Tree Grammars for Genetic Programming
Genetic Programming (GP) provides evolutionary methods for problems with tree representations. A recent development in Genetic Algorithms (GAs) has led to principled algorithms cal...
Peter A. N. Bosman, Edwin D. de Jong
ISBRA
2009
Springer
15 years 11 months ago
A Linear-Time Algorithm for Analyzing Array CGH Data Using Log Ratio Triangulation
Abstract. DNA copy number is the number of replicates of a contiguous segment of DNA on the genome. Copy number alteration (CNA) is a genetic abnormality in which the number of the...
Matthew Hayes, Jing Li
122
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IWINAC
2005
Springer
15 years 10 months ago
GA-Selection Revisited from an ES-Driven Point of View
Whereas the selection concept of Genetic Algorithms (GAs) and Genetic Programming (GP) is basically realized by the selection of above-average parents for reproduction, Evolution S...
Michael Affenzeller, Stefan Wagner 0002, Stephan M...
CIDM
2007
IEEE
15 years 11 months ago
K2GA: Heuristically Guided Evolution of Bayesian Network Structures from Data
— We present K2GA, an algorithm for learning Bayesian network structures from data. K2GA uses a genetic algorithm to perform stochastic search, while employing a modified versio...
Eli Faulkner
GECCO
2004
Springer
175views Optimization» more  GECCO 2004»
15 years 10 months ago
Enhanced Innovation: A Fusion of Chance Discovery and Evolutionary Computation to Foster Creative Processes and Decision Making
Abstract. Human-based genetic algorithms are powerful tools for organizational modeling. If we enhance them using chance discovery techniques, we obtain an innovative approach for ...
Xavier Llorà, Kei Ohnishi, Ying-Ping Chen, ...