129 search results - page 3 / 26 » Active learning with extremely sparse labeled examples |
ICML
2004
IEEE
15 years 3 months ago
2004
IEEE
The effort necessary to construct labeled sets of examples in a supervised learning scenario is often disregarded, though in many applications, it is a time-consuming and expensi...
60
Voted
ICML
2003
IEEE
15 years 10 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...
NAACL
2003
14 years 11 months ago
2003
This paper describes an application of active learning methods to the classification of phone strings recognized using unsupervised phonotactic models. The only training data req...
82
Voted
ICPR
2006
IEEE
15 years 10 months ago
2006
IEEE
Distance functions are an important component in many learning applications. However, the correct function is context dependent, therefore it is advantageous to learn a distance f...
CVPR
2008
IEEE
15 years 11 months ago
2008
IEEE
Discriminative approaches to human pose inference involve mapping visual observations to articulated body configurations. Current probabilistic approaches to learn this mapping ha...