41 search results - page 2 / 9 » Active Selection of Training Examples for Meta-Learning |
ICML
2003
IEEE
14 years 6 months ago
2003
IEEE
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...
ECML
2006
Springer
13 years 9 months ago
2006
Springer
Abstract. Active learning algorithms attempt to accelerate the learning process by requesting labels for the most informative items first. In real-world problems, however, there ma...
ICDM
2010
IEEE
13 years 3 months ago
2010
IEEE
Active learning has been proven a reliable strategy to reduce manual efforts in training data labeling. Such strategies incorporate the user as oracle: the classifier selects the m...
NIPS
2007
13 years 6 months ago
2007
We present a new and efficient semi-supervised training method for parameter estimation and feature selection in conditional random fields (CRFs). In real-world applications suc...
ECIR
2007
Springer
13 years 6 months ago
2007
Springer
Automated text categorisation systems learn a generalised hypothesis from large numbers of labelled examples. However, in many domains labelled data is scarce and expensive to obta...