45 search results - page 3 / 9 » Regularized Boost for Semi-Supervised Learning |
AAAI
2008
13 years 8 months ago
2008
The recent years have witnessed a surge of interests in semi-supervised learning methods. A common strategy for these algorithms is to require that the predicted data labels shoul...
JMLR
2010
13 years 1 months ago
2010
This paper proposes a novel algorithm for semisupervised learning. This algorithm learns graph cuts that maximize the margin with respect to the labels induced by the harmonic fun...
IJSI
2008
13 years 6 months ago
2008
Many data mining applications have a large amount of data but labeling data is often difficult, expensive, or time consuming, as it requires human experts for annotation. Semi-supe...
JMLR
2012
11 years 8 months ago
2012
In this paper we propose a new approach for semi-supervised structured output learning. Our approach uses relaxed labeling on unlabeled data to deal with the combinatorial nature ...
NIPS
2007
13 years 7 months ago
2007
Semi-supervised methods use unlabeled data in addition to labeled data to construct predictors. While existing semi-supervised methods have shown some promising empirical performa...