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» Classification by Discriminative Regularization
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PR
2006
229views more  PR 2006»
13 years 9 months ago
FS_SFS: A novel feature selection method for support vector machines
In many pattern recognition applications, high-dimensional feature vectors impose a high computational cost as well as the risk of "overfitting". Feature Selection addre...
Yi Liu, Yuan F. Zheng
TASLP
2008
149views more  TASLP 2008»
13 years 9 months ago
Using Articulatory Representations to Detect Segmental Errors in Nonnative Pronunciation
Abstract--Motivated by potential applications in second-language pedagogy, we present a novel approach to using articulatory information to improve automatic detection of typical p...
Joseph Tepperman, Shrikanth Narayanan
TIP
2008
128views more  TIP 2008»
13 years 9 months ago
Wavelet Frame Accelerated Reduced Support Vector Machines
In this paper, a novel method for reducing the runtime complexity of a support vector machine classifier is presented. The new training algorithm is fast and simple. This is achiev...
Matthias Rätsch, Gerd Teschke, Sami Romdhani,...
TSP
2008
180views more  TSP 2008»
13 years 9 months ago
Support Vector Machine Training for Improved Hidden Markov Modeling
We present a discriminative training algorithm, that uses support vector machines (SVMs), to improve the classification of discrete and continuous output probability hidden Markov ...
Alba Sloin, David Burshtein
PAMI
1998
131views more  PAMI 1998»
13 years 8 months ago
Characterization of Neuropathological Shape Deformations
—We present a framework for analyzing the shape deformation of structures within the human brain. A mathematical model is developed describing the deformation of any brain struct...
John Martin, Alex Pentland, Stan Sclaroff, Ron Kik...