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» Evolutionary Computation for Modeling and Optimization
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GECCO
2004
Springer
131views Optimization» more  GECCO 2004»
15 years 12 months ago
PolyEDA: Combining Estimation of Distribution Algorithms and Linear Inequality Constraints
Estimation of distribution algorithms (EDAs) are population-based heuristic search methods that use probabilistic models of good solutions to guide their search. When applied to co...
Jörn Grahl, Franz Rothlauf
SYNTHESE
2008
84views more  SYNTHESE 2008»
15 years 6 months ago
How experimental algorithmics can benefit from Mayo's extensions to Neyman-Pearson theory of testing
Although theoretical results for several algorithms in many application domains were presented during the last decades, not all algorithms can be analyzed fully theoretically. Exp...
Thomas Bartz-Beielstein
ICCS
2003
Springer
15 years 11 months ago
A Method of Hidden Markov Model Optimization for Use with Geophysical Data Sets
Geophysics research has been faced with a growing need for automated techniques with which to process large quantities of data. A successful tool must meet a number of requirements...
Robert A. Granat
AAAI
1998
15 years 7 months ago
Fast Probabilistic Modeling for Combinatorial Optimization
Probabilistic models have recently been utilized for the optimization of large combinatorial search problems. However, complex probabilistic models that attempt to capture interpa...
Shumeet Baluja, Scott Davies
IJCAI
2007
15 years 8 months ago
Model-Based Optimization of Testing through Reduction of Stimuli
The paper presents the theoretical foundations and an algorithm to reduce the efforts of testing physical systems. A test is formally described as a set of stimuli (inputs to the ...
Peter Struss