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COLT
2008
Springer
13 years 6 months ago
Does Unlabeled Data Provably Help? Worst-case Analysis of the Sample Complexity of Semi-Supervised Learning
We study the potential benefits to classification prediction that arise from having access to unlabeled samples. We compare learning in the semi-supervised model to the standard, ...
Shai Ben-David, Tyler Lu, Dávid Pál
EMNLP
2009
13 years 2 months ago
Graph Alignment for Semi-Supervised Semantic Role Labeling
Unknown lexical items present a major obstacle to the development of broadcoverage semantic role labeling systems. We address this problem with a semisupervised learning approach ...
Hagen Fürstenau, Mirella Lapata
NIPS
2007
13 years 6 months ago
Statistical Analysis of Semi-Supervised Regression
Semi-supervised methods use unlabeled data in addition to labeled data to construct predictors. While existing semi-supervised methods have shown some promising empirical performa...
John D. Lafferty, Larry A. Wasserman
AAAI
2008
13 years 7 months ago
Semi-Supervised Learning for Blog Classification
Blog classification (e.g., identifying bloggers' gender or age) is one of the most interesting current problems in blog analysis. Although this problem is usually solved by a...
Daisuke Ikeda, Hiroya Takamura, Manabu Okumura
COLING
2008
13 years 6 months ago
Extractive Summarization Using Supervised and Semi-Supervised Learning
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...
Kam-Fai Wong, Mingli Wu, Wenjie Li