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» Learning from Ambiguously Labeled Examples
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IDA
2005
Springer
13 years 10 months ago
Learning from Ambiguously Labeled Examples
Inducing a classification function from a set of examples in the form of labeled instances is a standard problem in supervised machine learning. In this paper, we are concerned w...
Eyke Hüllermeier, Jürgen Beringer
CVPR
2009
IEEE
14 years 11 months ago
Learning from Ambiguously Labeled Images
In many image and video collections, we have access only to partially labeled data. For example, personal photo collections often contain several faces per image and a caption t...
Benjamin Sapp, Benjamin Taskar, Chris Jordan, Timo...
AAAI
2007
13 years 6 months ago
Multi-Label Learning by Instance Differentiation
Multi-label learning deals with ambiguous examples each may belong to several concept classes simultaneously. In this learning framework, the inherent ambiguity of each example is...
Min-Ling Zhang, Zhi-Hua Zhou
NAACL
2010
13 years 2 months ago
The Effect of Ambiguity on the Automated Acquisition of WSD Examples
Several methods for automatically generating labeled examples that can be used as training data for WSD systems have been proposed, including a semisupervised approach based on re...
Mark Stevenson, Yikun Guo