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COLT
2005
Springer
14 years 2 months ago
Ranking and Scoring Using Empirical Risk Minimization
A general model is proposed for studying ranking problems. We investigate learning methods based on empirical minimization of the natural estimates of the ranking risk. The empiric...
Stéphan Clémençon, Gáb...
ROCAI
2004
Springer
14 years 2 months ago
Learning Interestingness Measures in Terminology Extraction. A ROC-based approach
Abstract. In the field of Text Mining, a key phase in data preparation is concerned with the extraction of terms, i.e. collocation of words attached to specific concepts (e.g. Ph...
Mathieu Roche, Jérôme Azé, Yve...
ICASSP
2011
IEEE
13 years 22 days ago
Low-rank matrix completion by variational sparse Bayesian learning
There has been a significant interest in the recovery of low-rank matrices from an incomplete of measurements, due to both theoretical and practical developments demonstrating th...
S. Derin Babacan, Martin Luessi, Rafael Molina, Ag...
PKDD
2009
Springer
118views Data Mining» more  PKDD 2009»
14 years 3 months ago
The Feature Importance Ranking Measure
Most accurate predictions are typically obtained by learning machines with complex feature spaces (as e.g. induced by kernels). Unfortunately, such decision rules are hardly access...
Alexander Zien, Nicole Krämer, Sören Son...
IAT
2009
IEEE
14 years 3 months ago
Automated Web Site Evaluation - An Approach Based on Ranking SVM
This paper proposes an automated web site evaluation approach using machine learning to cope with ranking problems. Evaluating web sites is a significant task for web service beca...
Peng Li, Seiji Yamada