543 search results - page 22 / 109 » A PAC-Style Model for Learning from Labeled and Unlabeled Da... |
ACL
2008
13 years 9 months ago
2008
We present a novel semi-supervised training algorithm for learning dependency parsers. By combining a supervised large margin loss with an unsupervised least squares loss, a discr...
CIKM
2000
Springer
14 years 8 days ago
2000
Springer
Recently there has been significant interest in supervised learning algorithms that combine labeled and unlabeled data for text learning tasks. The co-training setting [1] applie...
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
Given a model family and a set of unlabeled examples, one could either label specific examples or state general constraints--both provide information about the desired model. In g...
DSMML
2004
Springer
14 years 1 months ago
2004
Springer
The informative vector machine (IVM) is a practical method for Gaussian process regression and classification. The IVM produces a sparse approximation to a Gaussian process by com...
MM
2006
ACM
14 years 1 months ago
2006
ACM
Labeling objects in images is an essential prerequisite for many visual learning and recognition applications that depend on training data, such as image retrieval, object detecti...