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» Sparse Kernel SVMs via Cutting-Plane Training
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96
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RECOMB
2005
Springer
15 years 10 months ago
Learning Interpretable SVMs for Biological Sequence Classification
Background: Support Vector Machines (SVMs) ? using a variety of string kernels ? have been successfully applied to biological sequence classification problems. While SVMs achieve ...
Christin Schäfer, Gunnar Rätsch, Sö...
102
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ICANN
2007
Springer
15 years 2 months ago
Resilient Approximation of Kernel Classifiers
Abstract. Trained support vector machines (SVMs) have a slow runtime classification speed if the classification problem is noisy and the sample data set is large. Approximating the...
Thorsten Suttorp, Christian Igel
COLING
2008
14 years 11 months ago
Robust and Efficient Chinese Word Dependency Analysis with Linear Kernel Support Vector Machines
Data-driven learning based on shift reduce parsing algorithms has emerged dependency parsing and shown excellent performance to many Treebanks. In this paper, we investigate the e...
Yu-Chieh Wu, Jie-Chi Yang, Yue-Shi Lee
91
Voted
JMLR
2006
156views more  JMLR 2006»
14 years 10 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
2007
IEEE
15 years 11 months ago
Direct convex relaxations of sparse SVM
Although support vector machines (SVMs) for binary classification give rise to a decision rule that only relies on a subset of the training data points (support vectors), it will ...
Antoni B. Chan, Nuno Vasconcelos, Gert R. G. Lanck...