129 search results - page 4 / 26 » Active learning with extremely sparse labeled examples |
ECIR
2009
Springer
13 years 5 months ago
2009
Springer
Abstract. Active learning refers to the task of devising a ranking function that, given a classifier trained from relatively few training examples, ranks a set of additional unlabe...
CEAS
2007
Springer
13 years 11 months ago
2007
Springer
Active learning methods seek to reduce the number of labeled examples needed to train an effective classifier, and have natural appeal in spam filtering applications where trustwo...
IGARSS
2009
13 years 5 months ago
2009
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 ...
AAAI
1997
13 years 9 months ago
1997
In many real-world domains, supervised learning requires a large number of training examples. In this paper, we describe an active learning method that uses a committee of learner...
JMLR
2010
13 years 2 months ago
2010
We discuss multiclass-multilabel classification problems in which the set of classes is extremely large. Most existing multiclass-multilabel learning algorithms expect to observe ...