178 search results - page 6 / 36 » Extensions of Manifold Learning Algorithms in Kernel Feature... |
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
2007
IEEE
14 years 8 months ago
2007
IEEE
The choice of the kernel function which determines the mapping between the input space and the feature space is of crucial importance to kernel methods. The past few years have se...
BMVC
2010
13 years 5 months ago
2010
We present a framework for the reduction of dimensionality of a data set via manifold learning. Using the building blocks of local hyperplanes we show how a global manifold can be...
EDUTAINMENT
2007
Springer
14 years 1 months ago
2007
Springer
Due to the high-dimensionality of motion captured data which resulted in the complexity in motion analysis, a method of motion data processing based on manifold learning was propos...
EMNLP
2009
13 years 5 months ago
2009
We present a framework to extract the most important features (tree fragments) from a Tree Kernel (TK) space according to their importance in the target kernelbased machine, e.g. ...