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JMLR
2010
152views more  JMLR 2010»
14 years 10 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...
ICML
2009
IEEE
16 years 4 months ago
Prototype vector machine for large scale semi-supervised learning
Practical data mining rarely falls exactly into the supervised learning scenario. Rather, the growing amount of unlabeled data poses a big challenge to large-scale semi-supervised...
Kai Zhang, James T. Kwok, Bahram Parvin
EWCBR
2004
Springer
15 years 8 months ago
Exploiting Background Knowledge when Learning Similarity Measures
The definition of similarity measures—one core component of every CBR application—leads to a serious knowledge acquisition problem if domain and application specific requirem...
Thomas Gabel, Armin Stahl
152
Voted
JMLR
2012
13 years 5 months ago
A metric learning perspective of SVM: on the relation of LMNN and SVM
Support Vector Machines, SVMs, and the Large Margin Nearest Neighbor algorithm, LMNN, are two very popular learning algorithms with quite different learning biases. In this paper...
Huyen Do, Alexandros Kalousis, Jun Wang, Adam Wozn...
111
Voted
NIPS
2007
15 years 4 months ago
Bundle Methods for Machine Learning
We present a globally convergent method for regularized risk minimization problems. Our method applies to Support Vector estimation, regression, Gaussian Processes, and any other ...
Alex J. Smola, S. V. N. Vishwanathan, Quoc V. Le