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» Learning with Constrained and Unlabelled Data
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ACL
2011
13 years 1 months ago
Semi-Supervised Frame-Semantic Parsing for Unknown Predicates
We describe a new approach to disambiguating semantic frames evoked by lexical predicates previously unseen in a lexicon or annotated data. Our approach makes use of large amounts...
Dipanjan Das, Noah A. Smith
CIKM
2011
Springer
12 years 10 months ago
Imbalanced sentiment classification
Various semi-supervised learning methods have been proposed recently to solve the long-standing shortage problem of manually labeled data in sentiment classification. However, mos...
Shoushan Li, Guodong Zhou, Zhongqing Wang, Sophia ...
IROS
2009
IEEE
146views Robotics» more  IROS 2009»
14 years 4 months ago
Robust constraint-consistent learning
— Many everyday human skills can be framed in terms of performing some task subject to constraints imposed by the environment. Constraints are usually unobservable and frequently...
Matthew Howard, Stefan Klanke, Michael Gienger, Ch...
ICDM
2005
IEEE
217views Data Mining» more  ICDM 2005»
14 years 3 months ago
Improving Automatic Query Classification via Semi-Supervised Learning
Accurate topical classification of user queries allows for increased effectiveness and efficiency in general-purpose web search systems. Such classification becomes critical if th...
Steven M. Beitzel, Eric C. Jensen, Ophir Frieder, ...
ECML
2001
Springer
14 years 2 months ago
Iterative Double Clustering for Unsupervised and Semi-supervised Learning
We present a powerful meta-clustering technique called Iterative Double Clustering (IDC). The IDC method is a natural extension of the recent Double Clustering (DC) method of Slon...
Ran El-Yaniv, Oren Souroujon