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ICASSP
2008
IEEE
14 years 3 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
ACSW
2004
13 years 10 months ago
Detecting Stress in Spoken English using Decision Trees and Support Vector Machines
This paper describes an approach to the detection of stress in spoken New Zealand English. After identifying the vowel segments of the speech signal, the approach extracts two dif...
Huayang Xie, Peter Andreae, Mengjie Zhang, Paul Wa...
NIPS
2003
13 years 10 months ago
Nonlinear Filtering of Electron Micrographs by Means of Support Vector Regression
Nonlinear filtering can solve very complex problems, but typically involve very time consuming calculations. Here we show that for filters that are constructed as a RBF network ...
Roland Vollgraf, Michael Scholz, Ian A. Meinertzha...
CVPR
2005
IEEE
14 years 11 months ago
A Sparse Support Vector Machine Approach to Region-Based Image Categorization
Automatic image categorization using low-level features is a challenging research topic in computer vision. In this paper, we formulate the image categorization problem as a multi...
Jinbo Bi, Yixin Chen, James Ze Wang
JMLR
2010
115views more  JMLR 2010»
13 years 3 months ago
Fast and Scalable Local Kernel Machines
A computationally efficient approach to local learning with kernel methods is presented. The Fast Local Kernel Support Vector Machine (FaLK-SVM) trains a set of local SVMs on redu...
Nicola Segata, Enrico Blanzieri