358 search results - page 35 / 72 » Learning from labeled and unlabeled data on a directed graph |
108
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KDD
2009
ACM
16 years 10 days ago
2009
ACM
One common predictive modeling challenge occurs in text mining problems is that the training data and the operational (testing) data are drawn from different underlying distributi...
104
Voted
COLING
2008
15 years 1 months ago
2008
It is difficult to identify sentence importance from a single point of view. In this paper, we propose a learning-based approach to combine various sentence features. They are cat...
NIPS
2007
15 years 1 months ago
2007
Semi-supervised inductive learning concerns how to learn a decision rule from a data set containing both labeled and unlabeled data. Several boosting algorithms have been extended...
104
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DSMML
2004
Springer
15 years 5 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...
108
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ML
2010
ACM
14 years 6 months ago
2010
ACM
Graph representations of data are increasingly common. Such representations arise in a variety of applications, including computational biology, social network analysis, web applic...