296 search results - page 13 / 60 » Extractive Summarization Using Supervised and Semi-Supervise... |
100
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CVPR
2006
IEEE
15 years 11 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...
103
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ACL
2008
14 years 11 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...
EMNLP
2010
14 years 7 months ago
2010
Several recent discourse parsers have employed fully-supervised machine learning approaches. These methods require human annotators to beforehand create an extensive training corp...
143
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CVPR
2009
IEEE
16 years 5 months ago
2009
IEEE
Many semi-supervised learning algorithms only
deal with binary classification. Their extension to the
multi-class problem is usually obtained by repeatedly
solving a set of bina...
ICCV
2009
IEEE
16 years 2 months ago
2009
IEEE
Random Forests (RFs) have become commonplace
in many computer vision applications. Their
popularity is mainly driven by their high computational
efficiency during both training ...