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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,...
DICTA
2003
13 years 9 months ago
Algebraic Curve Fitting Support Vector Machines
An algebraic curve is defined as the zero set of a multivariate polynomial. We consider the problem of fitting an algebraic curve to a set of vectors given an additional set of v...
Christian J. Walder, Brian C. Lovell, Peter J. Koo...
CORR
2007
Springer
113views Education» more  CORR 2007»
13 years 7 months ago
Virtual screening with support vector machines and structure kernels
Support vector machines and kernel methods have recently gained considerable attention in chemoinformatics. They offer generally good performance for problems of supervised classi...
Pierre Mahé, Jean-Philippe Vert