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CDC
2010
IEEE
155views Control Systems» more  CDC 2010»
13 years 5 months ago
Linear parametric noise models for Least Squares Support Vector Machines
In the identification of nonlinear dynamical models it may happen that not only the system dynamics have to be modeled but also the noise has a dynamic character. We show how to ad...
Tillmann Falck, Johan A. K. Suykens, Bart De Moor
GFKL
2007
Springer
163views Data Mining» more  GFKL 2007»
14 years 2 months ago
Fast Support Vector Machine Classification of Very Large Datasets
In many classification applications, Support Vector Machines (SVMs) have proven to be highly performing and easy to handle classifiers with very good generalization abilities. Howe...
Janis Fehr, Karina Zapien Arreola, Hans Burkhardt
ICPR
2006
IEEE
14 years 11 months ago
Mixture of Support Vector Machines for HMM based Speech Recognition
Speech recognition is usually based on Hidden Markov Models (HMMs), which represent the temporal dynamics of speech very efficiently, and Gaussian mixture models, which do non-opt...
Sven E. Krüger, Martin Schafföner, Marce...
ESWA
2006
102views more  ESWA 2006»
13 years 10 months ago
A study of Taiwan's issuer credit rating systems using support vector machines
By providing credit risk information, credit rating systems benefit most participants in financial markets, including issuers, investors, market regulators and intermediaries. In ...
Wun-Hwa Chen, Jen-Ying Shih
BMCBI
2008
153views more  BMCBI 2008»
13 years 10 months ago
GAPscreener: An automatic tool for screening human genetic association literature in PubMed using the support vector machine tec
Background: Synthesis of data from published human genetic association studies is a critical step in the translation of human genome discoveries into health applications. Although...
Wei Yu, Melinda Clyne, Siobhan M. Dolan, Ajay Yesu...