124 search results - page 3 / 25 » Learning from Positive and Unlabeled Examples with Different... |
CVPR
2010
IEEE
13 years 4 months ago
2010
IEEE
This paper shows that the performance of a binary classifier can be significantly improved by the processing of structured unlabeled data, i.e. data are structured if knowing the ...
AUSAI
2008
Springer
13 years 8 months ago
2008
Springer
Classifiers are traditionally learned using sets of positive and negative training examples. However, often a classifier is required, but for training only an incomplete set of pos...
ILP
2001
Springer
13 years 10 months ago
2001
Springer
The Bayesian framework of learning from positive noise-free examples derived by Muggleton [12] is extended to learning functional hypotheses from positive examples containing norma...
NIPS
2003
13 years 7 months ago
2003
We describe a nonparametric Bayesian approach to generalizing from few labeled examples, guided by a larger set of unlabeled objects and the assumption of a latent tree-structure ...
KDD
2002
ACM
14 years 6 months ago
2002
ACM
In this paper, we present a new co-training strategy that makes use of unlabelled data. It trains two predictors in parallel, with each predictor labelling the unlabelled data for...