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» On Learning Boolean Functions
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CORR
2010
Springer
117views Education» more  CORR 2010»
15 years 6 months ago
Evolution with Drifting Targets
We consider the question of the stability of evolutionary algorithms to gradual changes, or drift, in the target concept. We define an algorithm to be resistant to drift if, for s...
Varun Kanade, Leslie G. Valiant, Jennifer Wortman ...
CORR
2010
Springer
80views Education» more  CORR 2010»
15 years 6 months ago
Separations of Matroid Freeness Properties
Properties of Boolean functions on the hypercube that are invariant with respect to linear transformations of the domain are among some of the most well-studied properties in the ...
Arnab Bhattacharyya, Elena Grigorescu, Jakob Nords...
GECCO
2010
Springer
155views Optimization» more  GECCO 2010»
15 years 11 months ago
Negative selection algorithms without generating detectors
Negative selection algorithms are immune-inspired classifiers that are trained on negative examples only. Classification is performed by generating detectors that match none of ...
Maciej Liskiewicz, Johannes Textor
ESANN
2006
15 years 8 months ago
Magnification control for batch neural gas
Neural gas (NG) constitutes a very robust clustering algorithm which can be derived as stochastic gradient descent from a cost function closely connected to the quantization error...
Barbara Hammer, Alexander Hasenfuss, Thomas Villma...
ICML
2003
IEEE
16 years 7 months ago
Optimizing Classifier Performance via an Approximation to the Wilcoxon-Mann-Whitney Statistic
When the goal is to achieve the best correct classification rate, cross entropy and mean squared error are typical cost functions used to optimize classifier performance. However,...
Lian Yan, Robert H. Dodier, Michael Mozer, Richard...