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» Visual nonlinear discriminant analysis for classifier design
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VLSISP
2010
254views more  VLSISP 2010»
13 years 3 months ago
Manifold Based Local Classifiers: Linear and Nonlinear Approaches
Abstract In case of insufficient data samples in highdimensional classification problems, sparse scatters of samples tend to have many ‘holes’—regions that have few or no nea...
Hakan Cevikalp, Diane Larlus, Marian Neamtu, Bill ...
CVPR
2010
IEEE
13 years 9 months ago
Bayes Optimal Kernel Discriminant Analysis
Kernel methods provide an efficient mechanism to derive nonlinear algorithms. In classification problems as well as in feature extraction, kernel-based approaches map the original...
Di You, Aleix Martinez
NIPS
2001
13 years 6 months ago
Discriminative Direction for Kernel Classifiers
In many scientific and engineering applications, detecting and understanding differences between two groups of examples can be reduced to a classical problem of training a classif...
Polina Golland
CEAS
2007
Springer
13 years 11 months ago
A Discriminative Classifier Learning Approach to Image Modeling and Spam Image Identification
We propose a discriminative classifier learning approach to image modeling for spam image identification. We analyze a large number of images extracted from the SpamArchive spam c...
Byungki Byun, Chin-Hui Lee, Steve Webb, Calton Pu
TITB
2008
102views more  TITB 2008»
13 years 5 months ago
Nonlinear Support Vector Machine Visualization for Risk Factor Analysis Using Nomograms and Localized Radial Basis Function Kern
Nonlinear classifiers, e.g., support vector machines (SVMs) with radial basis function (RBF) kernels, have been used widely for automatic diagnosis of diseases because of their hig...
Baek Hwan Cho, Hwanjo Yu, Jong Shill Lee, Young Jo...