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» Learning from Ambiguously Labeled Examples
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EMNLP
2009
13 years 8 months ago
Semi-supervised Semantic Role Labeling Using the Latent Words Language Model
Semantic Role Labeling (SRL) has proved to be a valuable tool for performing automatic analysis of natural language texts. Currently however, most systems rely on a large training...
Koen Deschacht, Marie-Francine Moens
ALT
2001
Springer
14 years 7 months ago
Real-Valued Multiple-Instance Learning with Queries
While there has been a significant amount of theoretical and empirical research on the multiple-instance learning model, most of this research is for concept learning. However, f...
Daniel R. Dooly, Sally A. Goldman, Stephen Kwek
AIRS
2006
Springer
14 years 2 months ago
Learning to Separate Text Content and Style for Classification
Many text documents naturally have two kinds of labels. For example, we may label web pages from universities according to their categories, such as "student" or "fa...
Dell Zhang, Wee Sun Lee
NAACL
2007
14 years 10 days ago
Can Semantic Roles Generalize Across Genres?
PropBank has been widely used as training data for Semantic Role Labeling. However, because this training data is taken from the WSJ, the resulting machine learning models tend to...
Szu-ting Yi, Edward Loper, Martha Palmer
ISMB
1993
14 years 7 days ago
Knowledge-Based Generation of Machine-Learning Experiments: Learning with DNA Crystallography Data
Thoughit has been possible in the past to learn to predict DNAhydration patterns from crystallographic data, there is ambiguity in the choice of training data (both in terms of th...
Dawn M. Cohen, Casimir A. Kulikowski, Helen Berman