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ICML
1996
IEEE
16 years 3 months ago
Representing and Learning Quality-Improving Search Control Knowledge
Generating good, production-quality plans is an essential element in transforming planners from research tools into real-world applications, but one that has been frequently overl...
M. Alicia Pérez
SYNTHESE
2008
84views more  SYNTHESE 2008»
15 years 3 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
IJCNN
2006
IEEE
15 years 9 months ago
Learning to Rank by Maximizing AUC with Linear Programming
— Area Under the ROC Curve (AUC) is often used to evaluate ranking performance in binary classification problems. Several researchers have approached AUC optimization by approxi...
Kaan Ataman, W. Nick Street, Yi Zhang
CSCLP
2006
Springer
15 years 6 months ago
Extracting Microstructure in Binary Constraint Networks
Abstract. We present algorithms that perform the extraction of partial assignments from binary Constraint Satisfaction Problems without introducing new constraints. They are based ...
Chavalit Likitvivatanavong, Roland H. C. Yap
GECCO
2005
Springer
153views Optimization» more  GECCO 2005»
15 years 8 months ago
Evolving neural network ensembles for control problems
In neuroevolution, a genetic algorithm is used to evolve a neural network to perform a particular task. The standard approach is to evolve a population over a number of generation...
David Pardoe, Michael S. Ryoo, Risto Miikkulainen