1235 search results - page 28 / 247 » Learning with Idealized Kernels |
ECML
2004
Springer
14 years 1 months ago
2004
Springer
The kernel function plays a central role in kernel methods. Most existing methods can only adapt the kernel parameters or the kernel matrix based on empirical data. Recently, Ong e...
FOCM
2006
13 years 10 months ago
2006
This paper considers the regularized learning algorithm associated with the leastsquare loss and reproducing kernel Hilbert spaces. The target is the error analysis for the regres...
IPL
2011
13 years 4 months ago
2011
We provide sample complexity of the problem of learning halfspaces with monotonic noise, using the regularized least squares algorithm in the reproducing kernel Hilbert spaces (RKH...
ICML
2008
IEEE
14 years 10 months ago
2008
IEEE
Point clouds are sets of points in two or three dimensions. Most kernel methods for learning on sets of points have not yet dealt with the specific geometrical invariances and pra...
ICML
2004
IEEE
14 years 10 months ago
2004
IEEE
Kernel conditional random fields (KCRFs) are introduced as a framework for discriminative modeling of graph-structured data. A representer theorem for conditional graphical models...