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» A kernel path algorithm for support vector machines
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TITB
2008
102views more  TITB 2008»
13 years 8 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...
ICASSP
2009
IEEE
14 years 3 months ago
Combining VTS model compensation and support vector machines
It is difficult to adapt discriminative classifiers, particularly kernel based ones such as support vector machines (SVMs), to handle mismatches between the training and test da...
Mark J. F. Gales, Federico Flego
ESANN
2000
13 years 10 months ago
Support Vector Committee Machines
Abstract. This paper proposes a mathematical programming framew ork for combining SVMs with possibly di erent kernels. Compared to single SVMs, the advantage of this approach is tw...
Dominique Martinez, Gilles Millerioux
GECCO
2007
Springer
180views Optimization» more  GECCO 2007»
14 years 20 days ago
Support vector regression for classifier prediction
In this paper we introduce XCSF with support vector prediction: the problem of learning the prediction function is solved as a support vector regression problem and each classifie...
Daniele Loiacono, Andrea Marelli, Pier Luca Lanzi
CVPR
2008
IEEE
14 years 10 months ago
Enforcing non-positive weights for stable support vector tracking
In this paper we demonstrate that the support vector tracking (SVT) framework first proposed by Avidan is equivalent to the canonical Lucas-Kanade (LK) algorithm with a weighted E...
Simon Lucey