53 search results - page 2 / 11 » Semi-supervised Learning for Handwriting Recognition |
IJSI
2008
13 years 5 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...
CVPR
2008
IEEE
14 years 7 months ago
2008
IEEE
Linear Discriminant Analysis (LDA), which works by maximizing the within-class similarity and minimizing the between-class similarity simultaneously, is a popular dimensionality r...
ICASSP
2010
IEEE
13 years 5 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...
ACL
2008
13 years 6 months ago
2008
This paper provides evidence that the use of more unlabeled data in semi-supervised learning can improve the performance of Natural Language Processing (NLP) tasks, such as part-o...
CVPR
2006
IEEE
14 years 7 months ago
2006
IEEE
We consider the general problem of learning from both labeled and unlabeled data. Given a set of data points, only a few of them are labeled, and the remaining points are unlabele...