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JMLR
2006
116views more  JMLR 2006»
13 years 8 months ago
Step Size Adaptation in Reproducing Kernel Hilbert Space
This paper presents an online support vector machine (SVM) that uses the stochastic meta-descent (SMD) algorithm to adapt its step size automatically. We formulate the online lear...
S. V. N. Vishwanathan, Nicol N. Schraudolph, Alex ...
BMCBI
2007
144views more  BMCBI 2007»
13 years 8 months ago
Motif kernel generated by genetic programming improves remote homology and fold detection
Background: Protein remote homology detection is a central problem in computational biology. Most recent methods train support vector machines to discriminate between related and ...
Tony Håndstad, Arne J. H. Hestnes, Pål...
BMCBI
2010
182views more  BMCBI 2010»
13 years 8 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...
ICASSP
2010
IEEE
13 years 6 months ago
A comparison of approaches for modeling prosodic features in speaker recognition
Prosodic information has been successfully used for speaker recognition for more than a decade. The best-performing prosodic system to date has been one based on features extracte...
Luciana Ferrer, Nicolas Scheffer, Elizabeth Shribe...
ISCI
2008
165views more  ISCI 2008»
13 years 8 months ago
Support vector regression from simulation data and few experimental samples
This paper considers nonlinear modeling based on a limited amount of experimental data and a simulator built from prior knowledge. The problem of how to best incorporate the data ...
Gérard Bloch, Fabien Lauer, Guillaume Colin...