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COLING
2002
13 years 8 months ago
Extracting Word Sequence Correspondences with Support Vector Machines
This paper proposes a learning and extracting method of word sequence correspondences from non-aligned parallel corpora with Support Vector Machines, which have high ability of th...
Kengo Sato, Hiroaki Saito
ML
2002
ACM
223views Machine Learning» more  ML 2002»
13 years 8 months ago
Text Categorization with Support Vector Machines. How to Represent Texts in Input Space?
The choice of the kernel function is crucial to most applications of support vector machines. In this paper, however, we show that in the case of text classification, term-frequenc...
Edda Leopold, Jörg Kindermann
ISNN
2005
Springer
14 years 2 months ago
Scaling the Kernel Function to Improve Performance of the Support Vector Machine
Abstract. The present study investigates a geometrical method for optimizing the kernel function of a support vector machine. The method is an improvement of the one proposed in [4...
Peter Williams, Sheng Li, Jianfeng Feng, Si Wu
CDC
2009
IEEE
126views Control Systems» more  CDC 2009»
13 years 10 months ago
Support vector machine classifiers for sequential decision problems
Classification problems in critical applications such as health care or security often require very high reliability because of the high costs of errors. In order to achieve this r...
Eladio Rodriguez Diaz, David A. Castaon
ICML
2003
IEEE
14 years 9 months ago
Low Bias Bagged Support Vector Machines
Theoretical and experimental analyses of bagging indicate that it is primarily a variance reduction technique. This suggests that bagging should be applied to learning algorithms ...
Giorgio Valentini, Thomas G. Dietterich