55 search results - page 3 / 11 » On Relevant Dimensions in Kernel Feature Spaces |
COLT
1999
Springer
13 years 9 months ago
1999
Springer
—Support vector (SV) machines are linear classifiers that use the maximum margin hyperplane in a feature space defined by a kernel function. Until recently, the only bounds on th...
BDA
2007
13 years 6 months ago
2007
In content-based retrieval, relevance feedback (RF) is a noticeable method for reducing the “semantic gap” between the low-level features describing the content and the usually...
ICANN
2005
Springer
13 years 10 months ago
2005
Springer
Abstract. In this paper, we consider the possibility of obtaining a kernel machine that is sparse in feature space and smooth in output space. Smooth in output space implies that t...
MLDM
1999
Springer
13 years 9 months ago
1999
Springer
Content-based image retrieval methods based on the Euclidean metric expect the feature space to be isotropic. They suer from unequal dierential relevance of features in comput...
NIPS
2000
13 years 6 months ago
2000
We propose a novel approach for categorizing text documents based on the use of a special kernel. The kernel is an inner product in the feature space generated by all subsequences...