1083 search results - page 2 / 217 » Learning Bounds for Support Vector Machines with Learned Ker... |
NIPS
1998
13 years 6 months ago
1998
The kernel-parameter is one of the few tunable parameters in Support Vector machines, controlling the complexity of the resulting hypothesis. Its choice amounts to model selection...
ALT
2001
Springer
14 years 2 months ago
2001
Springer
This paper concerns the design of a Support Vector Machine (SVM) appropriate for the learning of Boolean functions. This is motivated by the need of a more sophisticated algorithm ...
ICML
2007
IEEE
14 years 6 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...
PKDD
2009
Springer
13 years 12 months ago
2009
Springer
A serious drawback of kernel methods, and Support Vector Machines (SVM) in particular, is the difficulty in choosing a suitable kernel function for a given dataset. One of the appr...
PAKDD
2011
ACM
12 years 8 months ago
2011
ACM
A structural similarity kernel is presented in this paper for SVM learning, especially for learning with imbalanced datasets. Kernels in SVM are usually pairwise, comparing the sim...