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» Learning to learn with the informative vector machine
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ICPR
2006
IEEE
16 years 5 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...
170
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TNN
2008
97views more  TNN 2008»
15 years 4 months ago
Training Hard-Margin Support Vector Machines Using Greedy Stagewise Algorithm
Hard-margin support vector machines (HM-SVMs) suffer from getting overfitting in the presence of noise. Soft-margin SVMs deal with this problem by introducing a regularization term...
Liefeng Bo, Ling Wang, Licheng Jiao
BMCBI
2008
153views more  BMCBI 2008»
15 years 4 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...
ICASSP
2008
IEEE
15 years 11 months ago
Nested support vector machines
The one-class and cost-sensitive support vector machines (SVMs) are state-of-the-art machine learning methods for estimating density level sets and solving weighted classificatio...
Gyemin Lee, Clayton Scott
ACL
2009
15 years 2 months ago
A Novel Discourse Parser Based on Support Vector Machine Classification
This paper introduces a new algorithm to parse discourse within the framework of Rhetorical Structure Theory (RST). Our method is based on recent advances in the field of statisti...
David duVerle, Helmut Prendinger