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119
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GECCO
2009
Springer
188views Optimization» more  GECCO 2009»
15 years 6 months ago
Exploiting multiple classifier types with active learning
Many approaches to active learning involve training one classifier by periodically choosing new data points about which the classifier has the least confidence, but designing a co...
Zhenyu Lu, Josh Bongard
116
Voted
IJCNN
2007
IEEE
15 years 8 months ago
Preference Learning for Category-Ranking based Interactive Text Categorization
— Category Ranking is a variant of the multi-label classification problem, in which, rather than performing a (hard) assignment to an object of categories from a predefined set...
Fabio Aiolli, Fabrizio Sebastiani, Alessandro Sper...
CEC
2005
IEEE
15 years 8 months ago
XCS with computed prediction for the learning of Boolean functions
Computed prediction represents a major shift in learning classifier system research. XCS with computed prediction, based on linear approximators, has been applied so far to functi...
Pier Luca Lanzi, Daniele Loiacono, Stewart W. Wils...
106
Voted
IJCNN
2008
IEEE
15 years 9 months ago
Semi-supervised nearest neighbor editing
—This paper proposes a novel method for data editing. The goal of data editing in instance-based learning is to remove instances from a training set in order to increase the accu...
Donghai Guan, Weiwei Yuan, Young-Koo Lee, Sungyoun...
162
Voted
EMNLP
2006
15 years 3 months ago
Loss Minimization in Parse Reranking
We propose a general method for reranker construction which targets choosing the candidate with the least expected loss, rather than the most probable candidate. Different approac...
Ivan Titov, James Henderson