354 search results - page 5 / 71 » Learning classifiers from only positive and unlabeled data |
IJCAI
2003
13 years 8 months ago
2003
This paper summarizes a probabilistic approach for localizing people through the signal strengths of a wireless IEEE 802.11b network. Our approach uses data labeled by ground trut...
NIPS
2003
13 years 8 months ago
2003
We consider the general problem of learning from labeled and unlabeled data, which is often called semi-supervised learning or transductive inference. A principled approach to sem...
ALT
1998
Springer
13 years 11 months ago
1998
Springer
Learning from positive examples occurs very frequently in natural learning. The PAC learning model of Valiant takes many features of natural learning into account, but in most case...
CVPR
2008
IEEE
14 years 9 months ago
2008
IEEE
The required amount of labeled training data for object detection and classification is a major drawback of current methods. Combining labeled and unlabeled data via semisupervise...
ICANN
2009
Springer
14 years 2 days ago
2009
Springer
This paper proposes a modelling of Support Vector Machine (SVM) learning to address the problem of learning with sloppy labels. In binary classification, learning with sloppy labe...