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GECCO
2008
Springer
137views Optimization» more  GECCO 2008»
13 years 9 months ago
Informative sampling for large unbalanced data sets
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 ...
Zhenyu Lu, Anand I. Rughani, Bruce I. Tranmer, Jos...
BMCBI
2008
109views more  BMCBI 2008»
13 years 8 months ago
MetaFIND: A feature analysis tool for metabolomics data
Background: Metabolomics, or metabonomics, refers to the quantitative analysis of all metabolites present within a biological sample and is generally carried out using NMR spectro...
Kenneth Bryan, Lorraine Brennan, Padraig Cunningha...
SIGMOD
2007
ACM
192views Database» more  SIGMOD 2007»
14 years 8 months ago
Benchmarking declarative approximate selection predicates
Declarative data quality has been an active research topic. The fundamental principle behind a declarative approach to data quality is the use of declarative statements to realize...
Amit Chandel, Oktie Hassanzadeh, Nick Koudas, Moha...
ICPR
2010
IEEE
14 years 23 days ago
Selection of Training Instances for Music Genre Classification
In this paper we present a method for the selection of training instances based on the classification accuracy of a SVM classifier. The instances consist of feature vectors repres...
Miguel Lopes, Fabien Gouyon, Alessandro Koerich, L...
MM
2006
ACM
113views Multimedia» more  MM 2006»
14 years 2 months ago
Transductive inference using multiple experts for brushwork annotation in paintings domain
Many recent studies perform annotation of paintings based on brushwork. In these studies the brushwork is modeled indirectly as part of the annotation of high-level artistic conce...
Yelizaveta Marchenko, Tat-Seng Chua, Ramesh Jain