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ICANN
2009
Springer
14 years 2 months ago
Learning SVMs from Sloppily Labeled Data
This paper proposes a modelling of Support Vector Machine (SVM) learning to address the problem of learning with sloppy labels. In binary classification, learning with sloppy labe...
Guillaume Stempfel, Liva Ralaivola
ECML
2001
Springer
14 years 2 months ago
A Framework for Learning Rules from Multiple Instance Data
Abstract. This paper proposes a generic extension to propositional rule learners to handle multiple-instance data. In a multiple-instance representation, each learning example is r...
Yann Chevaleyre, Jean-Daniel Zucker
ECML
2007
Springer
14 years 1 months ago
Seeing the Forest Through the Trees: Learning a Comprehensible Model from an Ensemble
Abstract. Ensemble methods are popular learning methods that usually increase the predictive accuracy of a classifier though at the cost of interpretability and insight in the deci...
Anneleen Van Assche, Hendrik Blockeel
ECTEL
2007
Springer
14 years 4 months ago
Cross-System Validation of Engagement Prediction from Log Files
Engagement is an important aspect of effective learning. Time spent using an e-Learning system is not quality time if the learner is not engaged. Tracking student disengagement wou...
Mihaela Cocea, Stephan Weibelzahl
COLT
2008
Springer
13 years 11 months ago
Extracting Certainty from Uncertainty: Regret Bounded by Variation in Costs
Prediction from expert advice is a fundamental problem in machine learning. A major pillar of the field is the existence of learning algorithms whose average loss approaches that ...
Elad Hazan, Satyen Kale