591 search results - page 75 / 119 » Learning and optimization using the clonal selection princip... |
129
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GECCO
2008
Springer
15 years 3 months ago
2008
Springer
Selective sampling is a form of active learning which can reduce the cost of training by only drawing informative data points into the training set. This selected training set is ...
GECCO
2007
Springer
15 years 8 months ago
2007
Springer
In many design tasks it is difficult to explicitly define an objective function. This paper uses machine learning to derive an objective in a feature space based on selected examp...
133
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KDD
2005
ACM
15 years 7 months ago
2005
ACM
We present a probabilistic model-based framework for distributed learning that takes into account privacy restrictions and is applicable to scenarios where the different sites ha...
131
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ICANN
2005
Springer
15 years 7 months ago
2005
Springer
One aim of Meta-learning techniques is to minimize the time needed for problem solving, and the effort of parameter hand-tuning, by automating algorithm selection. The predictive m...
122
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MLDM
2005
Springer
15 years 7 months ago
2005
Springer
In the context of large databases, data preparation takes a greater importance : instances and explanatory attributes have to be carefully selected. In supervised learning, instanc...