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JMLR
2008
150views more  JMLR 2008»
13 years 9 months ago
Discriminative Learning of Max-Sum Classifiers
The max-sum classifier predicts n-tuple of labels from n-tuple of observable variables by maximizing a sum of quality functions defined over neighbouring pairs of labels and obser...
Vojtech Franc, Bogdan Savchynskyy
ROCAI
2004
Springer
14 years 2 months ago
Learning Mixtures of Localized Rules by Maximizing the Area Under the ROC Curve
We introduce a model class for statistical learning which is based on mixtures of propositional rules. In our mixture model, the weight of a rule is not uniform over the entire ins...
Tobias Sing, Niko Beerenwinkel, Thomas Lengauer
CIKM
2008
Springer
13 years 11 months ago
To swing or not to swing: learning when (not) to advertise
Web textual advertising can be interpreted as a search problem over the corpus of ads available for display in a particular context. In contrast to conventional information retrie...
Andrei Z. Broder, Massimiliano Ciaramita, Marcus F...
CIKM
2008
Springer
13 years 11 months ago
Learning a two-stage SVM/CRF sequence classifier
Learning a sequence classifier means learning to predict a sequence of output tags based on a set of input data items. For example, recognizing that a handwritten word is "ca...
Guilherme Hoefel, Charles Elkan
ECML
2003
Springer
14 years 2 months ago
Logistic Model Trees
Abstract. Tree induction methods and linear models are popular techniques for supervised learning tasks, both for the prediction of nominal classes and continuous numeric values. F...
Niels Landwehr, Mark Hall, Eibe Frank