1435 search results - page 1 / 287 » Generalization Error Bounds Using Unlabeled Data |
COLT
2005
Springer
13 years 10 months ago
2005
Springer
We present two new methods for obtaining generalization error bounds in a semi-supervised setting. Both methods are based on approximating the disagreement probability of pairs of ...
CORR
2006
Springer
13 years 5 months ago
2006
Springer
We consider semi-supervised classification when part of the available data is unlabeled. These unlabeled data can be useful for the classification problem when we make an assumpti...
NIPS
2004
13 years 6 months ago
2004
In the context of binary classification, we define disagreement as a measure of how often two independently-trained models differ in their classification of unlabeled data. We exp...
NIPS
2001
13 years 6 months ago
2001
The rule-based bootstrapping introduced by Yarowsky, and its cotraining variant by Blum and Mitchell, have met with considerable empirical success. Earlier work on the theory of c...
JMLR
2010
12 years 11 months ago
2010
In this paper, we propose a general framework for sparse semi-supervised learning, which concerns using a small portion of unlabeled data and a few labeled data to represent targe...