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JMLR
2010
152views more  JMLR 2010»
12 years 11 months ago
The SHOGUN Machine Learning Toolbox
We have developed a machine learning toolbox, called SHOGUN, which is designed for unified large-scale learning for a broad range of feature types and learning settings. It offers...
Sören Sonnenburg, Gunnar Rätsch, Sebasti...
JMLR
2006
156views more  JMLR 2006»
13 years 4 months ago
Large Scale Multiple Kernel Learning
While classical kernel-based learning algorithms are based on a single kernel, in practice it is often desirable to use multiple kernels. Lanckriet et al. (2004) considered conic ...
Sören Sonnenburg, Gunnar Rätsch, Christi...
ICML
2004
IEEE
14 years 5 months ago
Multiple kernel learning, conic duality, and the SMO algorithm
While classical kernel-based classifiers are based on a single kernel, in practice it is often desirable to base classifiers on combinations of multiple kernels. Lanckriet et al. ...
Francis R. Bach, Gert R. G. Lanckriet, Michael I. ...
NIME
2005
Springer
274views Music» more  NIME 2005»
13 years 10 months ago
MnM: a Max/MSP mapping toolbox
In this report, we describe our development on the Max/MSP toolbox MnM dedicated to mapping between gesture and sound, and more generally to statistical and machine learning metho...
Frédéric Bevilacqua, Remy Muller, No...
JMLR
2010
147views more  JMLR 2010»
12 years 11 months ago
Gaussian Processes for Machine Learning (GPML) Toolbox
The GPML toolbox provides a wide range of functionality for Gaussian process (GP) inference and prediction. GPs are specified by mean and covariance functions; we offer a library ...
Carl Edward Rasmussen, Hannes Nickisch