28 search results - page 1 / 6 » An SVD and Derivative Kernel Approach to Learning from Geome... |
NIPS
2004
13 years 5 months ago
2004
We present an algorithm based on convex optimization for constructing kernels for semi-supervised learning. The kernel matrices are derived from the spectral decomposition of grap...
JMLR
2006
13 years 4 months ago
2006
We propose a family of learning algorithms based on a new form of regularization that allows us to exploit the geometry of the marginal distribution. We focus on a semi-supervised...
CVPR
2007
IEEE
13 years 10 months ago
2007
IEEE
This paper describes a local ensemble kernel learning technique to recognize/classify objects from a large number of diverse categories. Due to the possibly large intraclass featu...
ICML
2004
IEEE
14 years 5 months ago
2004
IEEE
The problem of computing low rank approximations of matrices is considered. The novel aspect of our approach is that the low rank approximations are on a collection of matrices. W...
ICML
2005
IEEE
14 years 5 months ago
2005
IEEE
Due to its occurrence in engineering domains and implications for natural learning, the problem of utilizing unlabeled data is attracting increasing attention in machine learning....