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ICML
2010
IEEE
13 years 9 months ago
High-Performance Semi-Supervised Learning using Discriminatively Constrained Generative Models
We develop a semi-supervised learning method that constrains the posterior distribution of latent variables under a generative model to satisfy a rich set of feature expectation c...
Gregory Druck, Andrew McCallum
DAWAK
2006
Springer
14 years 12 days ago
Mining Direct Marketing Data by Ensembles of Weak Learners and Rough Set Methods
This paper describes problem of prediction that is based on direct marketing data coming from Nationwide Products and Services Questionnaire (NPSQ) prepared by Polish division of A...
Jerzy Blaszczynski, Krzysztof Dembczynski, Wojciec...
ML
2008
ACM
134views Machine Learning» more  ML 2008»
13 years 8 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...
BMCBI
2007
140views more  BMCBI 2007»
13 years 8 months ago
Prediction potential of candidate biomarker sets identified and validated on gene expression data from multiple datasets
Background: Independently derived expression profiles of the same biological condition often have few genes in common. In this study, we created populations of expression profiles...
Michael Gormley, William Dampier, Adam Ertel, Bilg...
DATAMINE
2006
117views more  DATAMINE 2006»
13 years 8 months ago
A Rule-Based Approach for Process Discovery: Dealing with Noise and Imbalance in Process Logs
Effective information systems require the existence of explicit process models. A completely specified process design needs to be developed in order to enact a given business proce...
Laura Maruster, A. J. M. M. Weijters, Wil M. P. va...