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» Optimization on Support Vector Machines
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EMO
2009
Springer
147views Optimization» more  EMO 2009»
15 years 4 months ago
Application of MOGA Search Strategy to SVM Training Data Selection
When training Support Vector Machine (SVM), selection of a training data set becomes an important issue, since the problem of overfitting exists with a large number of training da...
Tomoyuki Hiroyasu, Masashi Nishioka, Mitsunori Mik...
ICANN
2005
Springer
15 years 3 months ago
LS-SVM Hyperparameter Selection with a Nonparametric Noise Estimator
This paper presents a new method for the selection of the two hyperparameters of Least Squares Support Vector Machine (LS-SVM) approximators with Gaussian Kernels. The two hyperpar...
Amaury Lendasse, Yongnan Ji, Nima Reyhani, Michel ...
NIPS
2004
14 years 11 months ago
Nonparametric Transforms of Graph Kernels for Semi-Supervised Learning
We present an algorithm based on convex optimization for constructing kernels for semi-supervised learning. The kernel matrices are derived from the spectral decomposition of grap...
Xiaojin Zhu, Jaz S. Kandola, Zoubin Ghahramani, Jo...
ICPR
2010
IEEE
14 years 8 months ago
Learning the Kernel Combination for Object Categorization
Although Support Vector Machines(SVM) succeed in classifying several image databases using image descriptors proposed in the literature, no single descriptor can be optimal for ge...
Deyuan Zhang, Xiaolong Wang, Bingquan Liu
IR
2010
14 years 7 months ago
Efficient algorithms for ranking with SVMs
RankSVM (Herbrich et al, 2000; Joachims, 2002) is a pairwise method for designing ranking models. SVMLight is the only publicly available software for RankSVM. It is slow and, due ...
Olivier Chapelle, S. Sathiya Keerthi