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» Incremental Training of Multiclass Support Vector Machines
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ICML
2000
IEEE
15 years 10 months ago
Less is More: Active Learning with Support Vector Machines
We describe a simple active learning heuristic which greatly enhances the generalization behavior of support vector machines (SVMs) on several practical document classification ta...
Greg Schohn, David Cohn
ICMLA
2008
14 years 11 months ago
Inferring Sparse Kernel Combinations and Relevance Vectors: An Application to Subcellular Localization of Proteins
In this paper, we introduce two new formulations for multi-class multi-kernel relevance vector machines (mRVMs) that explicitly lead to sparse solutions, both in samples and in nu...
Theodoros Damoulas, Yiming Ying, Mark A. Girolami,...
ICPR
2008
IEEE
15 years 3 months ago
A fast revised simplex method for SVM training
Active set methods for training the Support Vector Machines (SVM) are advantageous since they enable incremental training and, as we show in this research, do not exhibit exponent...
Christopher Sentelle, Georgios C. Anagnostopoulos,...
INFORMATICALT
2011
91views more  INFORMATICALT 2011»
14 years 4 months ago
A Quadratic Loss Multi-Class SVM for which a Radius-Margin Bound Applies
To set the values of the hyperparameters of a support vector machine (SVM), the method of choice is cross-validation. Several upper bounds on the leave-one-out error of the pattern...
Yann Guermeur, Emmanuel Monfrini
BMCBI
2007
93views more  BMCBI 2007»
14 years 9 months ago
SVM-Fold: a tool for discriminative multi-class protein fold and superfamily recognition
Background: Predicting a protein’s structural class from its amino acid sequence is a fundamental problem in computational biology. Much recent work has focused on developing ne...
Iain Melvin, Eugene Ie, Rui Kuang, Jason Weston, W...