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» Training of Support Vector Machines with Mahalanobis Kernels
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ICML
2004
IEEE
15 years 10 months ago
Multi-task feature and kernel selection for SVMs
We compute a common feature selection or kernel selection configuration for multiple support vector machines (SVMs) trained on different yet inter-related datasets. The method is ...
Tony Jebara
ICPR
2006
IEEE
15 years 10 months ago
Hybrid Kernel Machine Ensemble for Imbalanced Data Sets
A two-class imbalanced data problem (IDP) emerges when the data from majority class are compactly clustered and the data from minority class are scattered. Though a discriminative...
Kap Luk Chan, Peng Li, Wen Fang
ICML
2010
IEEE
14 years 10 months ago
COFFIN: A Computational Framework for Linear SVMs
In a variety of applications, kernel machines such as Support Vector Machines (SVMs) have been used with great success often delivering stateof-the-art results. Using the kernel t...
Sören Sonnenburg, Vojtech Franc
ICML
2007
IEEE
15 years 10 months ago
Support cluster machine
For large-scale classification problems, the training samples can be clustered beforehand as a downsampling pre-process, and then only the obtained clusters are used for training....
Bin Li, Mingmin Chi, Jianping Fan, Xiangyang Xue
PRL
2006
114views more  PRL 2006»
14 years 9 months ago
Incremental training of support vector machines using hyperspheres
In the conventional incremental training of support vector machines, candidates for support vectors tend to be deleted if the separating hyperplane rotates as the training data ar...
Shinya Katagiri, Shigeo Abe