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COLING
2002
13 years 7 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
121views Machine Learning» more  ML 2002»
13 years 7 months ago
Choosing Multiple Parameters for Support Vector Machines
The problem of automatically tuning multiple parameters for pattern recognition Support Vector Machines (SVMs) is considered. This is done by minimizing some estimates of the gener...
Olivier Chapelle, Vladimir Vapnik, Olivier Bousque...
ML
2002
ACM
104views Machine Learning» more  ML 2002»
13 years 7 months ago
A Simple Decomposition Method for Support Vector Machines
The decomposition method is currently one of the major methods for solving support vector machines. An important issue of this method is the selection of working sets. In this pape...
Chih-Wei Hsu, Chih-Jen Lin
ML
2002
ACM
223views Machine Learning» more  ML 2002»
13 years 7 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
ICASSP
2011
IEEE
12 years 11 months ago
Support vector regression fusion scheme in phone duration modeling
A fusion scheme of phone duration models (PDMs) is presented in this work. Specifically, a support vector regression (SVR)-fusion model is fed with the predictions of a group of i...
Alexandros Lazaridis, Iosif Mporas, Todor Ganchev,...