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» Robust Regularized Kernel Regression
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BMCBI
2010
182views more  BMCBI 2010»
13 years 6 months ago
L2-norm multiple kernel learning and its application to biomedical data fusion
Background: This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields diff...
Shi Yu, Tillmann Falck, Anneleen Daemen, Lé...
ML
2006
ACM
163views Machine Learning» more  ML 2006»
13 years 6 months ago
Extremely randomized trees
Abstract This paper proposes a new tree-based ensemble method for supervised classification and regression problems. It essentially consists of randomizing strongly both attribute ...
Pierre Geurts, Damien Ernst, Louis Wehenkel
BMCBI
2007
154views more  BMCBI 2007»
13 years 6 months ago
Inferring biological networks with output kernel trees
Background: Elucidating biological networks between proteins appears nowadays as one of the most important challenges in systems biology. Computational approaches to this problem ...
Pierre Geurts, Nizar Touleimat, Marie Dutreix, Flo...
AAAI
2006
13 years 8 months ago
Multi-Conditional Learning: Generative/Discriminative Training for Clustering and Classification
This paper presents multi-conditional learning (MCL), a training criterion based on a product of multiple conditional likelihoods. When combining the traditional conditional proba...
Andrew McCallum, Chris Pal, Gregory Druck, Xuerui ...
DAGM
2011
Springer
12 years 6 months ago
Using Landmarks as a Deformation Prior for Hybrid Image Registration
Hybrid registration schemes are a powerful alternative to fully automatic registration algorithms. Current methods for hybrid registration either include the landmark information a...
Marcel Lüthi, Christoph Jud, Thomas Vetter