1484 search results - page 2 / 297 » Semi-supervised Learning from General Unlabeled Data |
NIPS
2007
13 years 6 months ago
2007
Semi-supervised inductive learning concerns how to learn a decision rule from a data set containing both labeled and unlabeled data. Several boosting algorithms have been extended...
COLT
2008
Springer
13 years 7 months ago
2008
Springer
We study the potential benefits to classification prediction that arise from having access to unlabeled samples. We compare learning in the semi-supervised model to the standard, ...
ICASSP
2010
IEEE
13 years 5 months ago
2010
IEEE
Supervised learning uses a training set of labeled examples to compute a classifier which is a mapping from feature vectors to class labels. The success of a learning algorithm i...
ICDM
2005
IEEE
13 years 11 months ago
2005
IEEE
Accurate topical classification of user queries allows for increased effectiveness and efficiency in general-purpose web search systems. Such classification becomes critical if th...
AMT
2006
Springer
13 years 9 months ago
2006
Springer
Text classification using positive and unlabeled data refers to the problem of building text classifier using positive documents (P) of one class and unlabeled documents (U) of man...