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IDA
2007
Springer
15 years 7 months ago
Removing biases in unsupervised learning of sequential patterns
Unsupervised sequence learning is important to many applications. A learner is presented with unlabeled sequential data, and must discover sequential patterns that characterize th...
Yoav Horman, Gal A. Kaminka
CORR
2011
Springer
183views Education» more  CORR 2011»
14 years 11 months ago
Learning When Training Data are Costly: The Effect of Class Distribution on Tree Induction
For large, real-world inductive learning problems, the number of training examples often must be limited due to the costs associated with procuring, preparing, and storing the tra...
Foster J. Provost, Gary M. Weiss
PAMI
2008
170views more  PAMI 2008»
15 years 7 months ago
Unsupervised Category Modeling, Recognition, and Segmentation in Images
Suppose a set of arbitrary (unlabeled) images contains frequent occurrences of 2D objects from an unknown category. This paper is aimed at simultaneously solving the following rel...
Sinisa Todorovic, Narendra Ahuja
JCAL
2002
98views more  JCAL 2002»
15 years 6 months ago
A comparison of temporal speech and text cueing in educational multimedia
This research focused on the prediction that children in their school setting would learn more from educational multimedia when critical information was presented as spoken instead...
Bruce L. Mann, P. Newhouse, J. Pagram, A. Campbell...
ESWS
2009
Springer
16 years 1 months ago
Improving Ontology Matching Using Meta-level Learning
Despite serious research efforts, automatic ontology matching still suffers from severe problems with respect to the quality of matching results. Existing matching systems trade-of...
Kai Eckert, Christian Meilicke, Heiner Stuckenschm...