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» Learning Models for Ranking Aggregates
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ADMA
2005
Springer
157views Data Mining» more  ADMA 2005»
15 years 9 months ago
Learning k-Nearest Neighbor Naive Bayes for Ranking
Accurate probability-based ranking of instances is crucial in many real-world data mining applications. KNN (k-nearest neighbor) [1] has been intensively studied as an effective c...
Liangxiao Jiang, Harry Zhang, Jiang Su
ECTEL
2010
Springer
15 years 1 months ago
GVIS: A Facility for Adaptively Mashing Up and Representing Open Learner Models
In this article we present an infrastructure for creating mash up and visual representations of the user profile that combine data from different sources. We explored this approach...
Luca Mazzola, Riccardo Mazza
ICANN
2009
Springer
15 years 8 months ago
Learning from Examples to Generalize over Pose and Illumination
We present a neural system that recognizes faces under strong variations in pose and illumination. The generalization is learnt completely on the basis of examples of a subset of p...
Marco K. Müller, Rolf P. Würtz
ML
2008
ACM
134views Machine Learning» more  ML 2008»
15 years 4 months ago
Multilabel classification via calibrated label ranking
Label ranking studies the problem of learning a mapping from instances to rankings over a predefined set of labels. Hitherto existing approaches to label ranking implicitly operat...
Johannes Fürnkranz, Eyke Hüllermeier, En...
CIKM
2009
Springer
15 years 10 months ago
On domain similarity and effectiveness of adapting-to-rank
Adapting to rank address the the problem of insufficient domainspecific labeled training data in learning to rank. However, the initial study shows that adaptation is not always...
Keke Chen, Jing Bai, Srihari Reddy, Belle L. Tseng