148 search results - page 5 / 30 » Feature space perspectives for learning the kernel |
ICASSP
2011
IEEE
12 years 11 months ago
2011
IEEE
Kernel nonnegative matrix factorization (KNMF) is a recent kernel extension of NMF, where matrix factorization is carried out in a reproducing kernel Hilbert space (RKHS) with a f...
ICML
2003
IEEE
14 years 8 months ago
2003
IEEE
When the training instances of the target class are heavily outnumbered by non-target training instances, SVMs can be ineffective in determining the class boundary. To remedy this...
ICML
2003
IEEE
14 years 8 months ago
2003
IEEE
Distance-based methods in machine learning and pattern recognition have to rely on a metric distance between points in the input space. Instead of specifying a metric a priori, we...
JMLR
2010
13 years 2 months ago
2010
Appropriate selection of the kernel function, which implicitly defines the feature space of an algorithm, has a crucial role in the success of kernel methods. In this paper, we co...
CORR
2012
Springer
12 years 3 months ago
2012
Springer
Approximating non-linear kernels using feature maps has gained a lot of interest in recent years due to applications in reducing training and testing times of SVM classifiers and...