297 search results - page 39 / 60 » Learning from Ambiguously Labeled Examples |
ECML
2007
Springer
14 years 5 months ago
2007
Springer
Co-training is a semi-supervised learning paradigm which trains two learners respectively from two different views and lets the learners label some unlabeled examples for each oth...
KDD
2008
ACM
14 years 11 months ago
2008
ACM
The effectiveness of knowledge transfer using classification algorithms depends on the difference between the distribution that generates the training examples and the one from wh...
ICDM
2009
IEEE
13 years 8 months ago
2009
IEEE
In this paper we study the problem of classifier learning where the input data contains unjustified dependencies between some data attributes and the class label. Such cases arise...
ICDM
2006
IEEE
14 years 5 months ago
2006
IEEE
Current outlier detection schemes typically output a numeric score representing the degree to which a given observation is an outlier. We argue that converting the scores into wel...
ICASSP
2010
IEEE
13 years 11 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...