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172
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ICPR
2006
IEEE
16 years 8 months ago
A New Data Selection Principle for Semi-Supervised Incremental Learning
Current semi-supervised incremental learning approaches select unlabeled examples with predicted high confidence for model re-training. We show that for many applications this dat...
Alexander I. Rudnicky, Rong Zhang
ALT
2002
Springer
16 years 4 months ago
A Pathology of Bottom-Up Hill-Climbing in Inductive Rule Learning
In this paper, we close the gap between the simple and straight-forward implementations of top-down hill-climbing that can be found in the literature, and the rather complex strate...
Johannes Fürnkranz
ICASSP
2008
IEEE
16 years 1 months ago
Music preference learning with partial information
We consider the problem of online learning in a changing environment under sparse user feedback. Specifically, we address the classification of music types according to a user...
Yvonne Moh, Peter Orbanz, Joachim M. Buhmann
163
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ECTEL
2007
Springer
16 years 1 months ago
Learning from the Past: TEL Implementation 1997 and 2007
This paper argues that the key challenges facing HE institutions in 2007 are the same as a decade previously and therefore that lessons may be learned from previous attempts to emp...
Stephen Brown
CVPR
2006
IEEE
15 years 10 months ago
Region-based Image Annotation using Asymmetrical Support Vector Machine-based Multiple-Instance Learning
In region-based image annotation, keywords are usually associated with images instead of individual regions in the training data set. This poses a major challenge for any learning...
Changbo Yang, Ming Dong, Jing Hua