843 search results - page 46 / 169 » Learning aspect models with partially labeled data |
130
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SDM
2010
SIAM
15 years 5 months ago
2010
SIAM
Lack of labeled training examples is a common problem for many applications. In the same time, there is usually an abundance of labeled data from related tasks. But they have diff...
135
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ICDM
2005
IEEE
15 years 9 months ago
2005
IEEE
The preference model introduced in this paper gives a natural framework and a principled solution for a broad class of supervised learning problems with structured predictions, su...
141
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NLE
2008
15 years 4 months ago
2008
Being able to identify which rhetorical relations (e.g., contrast or explanation) hold between spans of text is important for many natural language processing applications. Using ...
159
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ICML
2007
IEEE
16 years 4 months ago
2007
IEEE
Supervised learning is difficult with high dimensional input spaces and very small training sets, but accurate classification may be possible if the data lie on a low-dimensional ...
161
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AAAI
2011
14 years 4 months ago
2011
A common approach in machine learning is to use a large amount of labeled data to train a model. Usually this model can then only be used to classify data in the same feature spac...