358 search results - page 26 / 72 » Learning from labeled and unlabeled data on a directed graph |
209
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ACL
2011
14 years 9 months ago
2011
We describe a new approach to disambiguating semantic frames evoked by lexical predicates previously unseen in a lexicon or annotated data. Our approach makes use of large amounts...
186
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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...
197
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CVPR
2009
IEEE
17 years 1 months ago
2009
IEEE
Graph-based methods form a main category of semisupervised
learning, offering flexibility and easy implementation
in many applications. However, the performance of
these methods...
159
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ICDM
2006
IEEE
16 years 6 days ago
2006
IEEE
In active learning, a machine learning algorithm is given an unlabeled set of examples U, and is allowed to request labels for a relatively small subset of U to use for training. ...
149
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PKDD
2010
Springer
15 years 4 months ago
2010
Springer
Most approaches to classifying media content assume a fixed, closed vocabulary of labels. In contrast, we advocate machine learning approaches which take advantage of the millions...