543 search results - page 22 / 109 » A PAC-Style Model for Learning from Labeled and Unlabeled Da... |
182
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ACL
2008
15 years 7 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...
169
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CIKM
2000
Springer
15 years 10 months 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...
151
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ICML
2009
IEEE
16 years 6 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...
168
Voted
DSMML
2004
Springer
15 years 11 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...
182
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MM
2006
ACM
16 years 1 days 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...