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» Learning with Rigorous Support Vector Machines
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RECOMB
2005
Springer
16 years 4 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...
128
Voted
NIPS
2000
15 years 5 months ago
Regularized Winnow Methods
In theory, the Winnow multiplicative update has certain advantages over the Perceptron additive update when there are many irrelevant attributes. Recently, there has been much eff...
Tong Zhang
ICML
2007
IEEE
16 years 4 months ago
Fast and effective kernels for relational learning from texts
In this paper, we define a family of syntactic kernels for automatic relational learning from pairs of natural language sentences. We provide an efficient computation of such mode...
Alessandro Moschitti, Fabio Massimo Zanzotto
122
Voted
ICML
2003
IEEE
16 years 4 months ago
Multi-Objective Programming in SVMs
We propose a general framework for support vector machines (SVM) based on the principle of multi-objective optimization. The learning of SVMs is formulated as a multiobjective pro...
Jinbo Bi
144
Voted
ICML
2007
IEEE
16 years 4 months ago
Sparse probabilistic classifiers
The scores returned by support vector machines are often used as a confidence measures in the classification of new examples. However, there is no theoretical argument sustaining ...
Romain Hérault, Yves Grandvalet