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» Considering Cost Asymmetry in Learning Classifiers
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ICML
2009
IEEE
14 years 5 months ago
Uncertainty sampling and transductive experimental design for active dual supervision
Dual supervision refers to the general setting of learning from both labeled examples as well as labeled features. Labeled features are naturally available in tasks such as text c...
Vikas Sindhwani, Prem Melville, Richard D. Lawrenc...
JMLR
2010
136views more  JMLR 2010»
12 years 11 months ago
Reducing Label Complexity by Learning From Bags
We consider a supervised learning setting in which the main cost of learning is the number of training labels and one can obtain a single label for a bag of examples, indicating o...
Sivan Sabato, Nathan Srebro, Naftali Tishby
ESANN
2006
13 years 6 months ago
Margin based Active Learning for LVQ Networks
In this article, we extend a local prototype-based learning model by active learning, which gives the learner the capability to select training samples during the model adaptation...
Frank-Michael Schleif, Barbara Hammer, Thomas Vill...