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GECCO
2009
Springer
188views Optimization» more  GECCO 2009»
14 years 1 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
IGARSS
2009
13 years 7 months ago
Active Learning of Hyperspectral Data with Spatially Dependent Label Acquisition Costs
Supervised learners can be used to automatically classify many types of spatially distributed data. For example, land cover classification by hyperspectral image data analysis is ...
Alexander Liu, Goo Jun, Joydeep Ghosh
ICML
2003
IEEE
14 years 11 months ago
Incorporating Diversity in Active Learning with Support Vector Machines
In many real world applications, active selection of training examples can significantly reduce the number of labelled training examples to learn a classification function. Differ...
Klaus Brinker
MIR
2005
ACM
129views Multimedia» more  MIR 2005»
14 years 3 months ago
Multi-graph enabled active learning for multimodal web image retrieval
In this paper, we propose a multimodal Web image retrieval technique based on multi-graph enabled active learning. The main goal is to leverage the heterogeneous data on the Web t...
Xin-Jing Wang, Wei-Ying Ma, Lei Zhang, Xing Li
KCAP
2009
ACM
14 years 4 months ago
Reducing class imbalance during active learning for named entity annotation
In lots of natural language processing tasks, the classes to be dealt with often occur heavily imbalanced in the underlying data set and classifiers trained on such skewed data t...
Katrin Tomanek, Udo Hahn