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ECML
2007
Springer
13 years 11 months ago
Dual Strategy Active Learning
Abstract. Active Learning methods rely on static strategies for sampling unlabeled point(s). These strategies range from uncertainty sampling and density estimation to multi-factor...
Pinar Donmez, Jaime G. Carbonell, Paul N. Bennett
AMAI
1998
Springer
13 years 4 months ago
Generalization and Specialization Strategies for Learning r.e. Languages
Overgeneralization is a major issue in the identification of grammars for formal languages from positive data. Different formulations of generalization and specialization strate...
Sanjay Jain, Arun Sharma
PKDD
2010
Springer
143views Data Mining» more  PKDD 2010»
13 years 2 months ago
A Unified Approach to Active Dual Supervision for Labeling Features and Examples
Abstract. When faced with the task of building accurate classifiers, active learning is often a beneficial tool for minimizing the requisite costs of human annotation. Traditional ...
Josh Attenberg, Prem Melville, Foster J. Provost
PAKDD
2004
ACM
143views Data Mining» more  PAKDD 2004»
13 years 10 months ago
Compact Dual Ensembles for Active Learning
Generic ensemble methods can achieve excellent learning performance, but are not good candidates for active learning because of their different design purposes. We investigate how...
Amit Mandvikar, Huan Liu, Hiroshi Motoda
ICML
2009
IEEE
14 years 5 months ago
Uncertainty sampling and transductive experimental design for active dual supervision
Dual supervision refers to the general setting of learning from both labeled examples as well as labeled features. Labeled features are naturally available in tasks such as text c...
Vikas Sindhwani, Prem Melville, Richard D. Lawrenc...