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» Using Machine Learning to Focus Iterative Optimization
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118
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EGC
2005
Springer
15 years 7 months ago
A Grid-Oriented Genetic Algorithm
Genetic algorithms (GAs) are stochastic search methods that have been successfully applied in many search, optimization, and machine learning problems. Their parallel counterpart (...
Jose Herrera, Eduardo Huedo, Rubén S. Monte...
GECCO
2005
Springer
126views Optimization» more  GECCO 2005»
15 years 7 months ago
Is negative selection appropriate for anomaly detection?
Negative selection algorithms for hamming and real-valued shape-spaces are reviewed. Problems are identified with the use of these shape-spaces, and the negative selection algori...
Thomas Stibor, Philipp H. Mohr, Jonathan Timmis, C...
115
Voted
CP
2006
Springer
15 years 6 months ago
Performance Prediction and Automated Tuning of Randomized and Parametric Algorithms
Abstract. Machine learning can be utilized to build models that predict the runtime of search algorithms for hard combinatorial problems. Such empirical hardness models have previo...
Frank Hutter, Youssef Hamadi, Holger H. Hoos, Kevi...
DATAMINE
2010
122views more  DATAMINE 2010»
15 years 2 months ago
Three naive Bayes approaches for discrimination-free classification
In this paper, we investigate how to modify the Naive Bayes classifier in order to perform classification that is restricted to be independent with respect to a given sensitive att...
Toon Calders, Sicco Verwer
WWW
2009
ACM
16 years 2 months ago
Combining anchor text categorization and graph analysis for paid link detection
In order to artificially boost the rank of commercial pages in search engine results, search engine optimizers pay for links to these pages on other websites. Identifying paid lin...
Kirill Nikolaev, Ekaterina Zudina, Andrey Gorshkov