54 search results - page 1 / 11 » Semi-supervised learning by locally linear embedding in kern... |
ICPR
2008
IEEE
13 years 11 months ago
2008
IEEE
Graph based semi-supervised learning methods (SSL) implicitly assume that the intrinsic geometry of the data points can be fully specified by an Euclidean distance based local ne...
ICCV
2005
IEEE
14 years 6 months ago
2005
IEEE
Recently there has been a lot of interest in geometrically motivated approaches to data analysis in high dimensional spaces. We consider the case where data is drawn from sampling...
ICML
2004
IEEE
13 years 10 months ago
2004
IEEE
We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Noting that the kernel matrix implicitly maps the data into ...
ICML
2002
IEEE
14 years 5 months ago
2002
IEEE
Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is perfor...
ICML
2008
IEEE
14 years 5 months ago
2008
IEEE
Recently, instead of selecting a single kernel, multiple kernel learning (MKL) has been proposed which uses a convex combination of kernels, where the weight of each kernel is opt...