990 search results - page 11 / 198 » Learning with non-positive kernels |
JMLR
2010
13 years 5 months ago
2010
A large number of learning algorithms, for example, spectral clustering, kernel Principal Components Analysis and many manifold methods are based on estimating eigenvalues and eig...
PR
2010
13 years 5 months ago
2010
Most existing representative works in semi-supervised clustering do not sufficiently solve the violation problem of pairwise constraints. On the other hand, traditional kernel met...
SDM
2012
SIAM
11 years 9 months ago
2012
SIAM
Kernel summations are a ubiquitous key computational bottleneck in many data analysis methods. In this paper, we attempt to marry, for the first time, the best relevant technique...
DAGM
2011
Springer
12 years 7 months ago
2011
Springer
Many unsupervised learning algorithms make use of kernels that rely on the Euclidean distance between two samples. However, the Euclidean distance is optimal for Gaussian distribut...
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
The Support Vector Machine (SVM) is an acknowledged powerful tool for building classifiers, but it lacks flexibility, in the sense that the kernel is chosen prior to learning. Mul...