335 search results - page 8 / 67 » Kernel Machines and Boolean Functions |
ICCV
2009
IEEE
13 years 5 months ago
2009
IEEE
The use of Mercer kernel methods in statistical learning theory provides for strong learning capabilities, as seen in kernel principal component analysis and support vector machin...
ICANN
2005
Springer
14 years 29 days 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...
ICANN
2007
Springer
14 years 1 months ago
2007
Springer
Support Vector Machines (SVMs) for classification tasks produce sparse models by maximizing the margin. Two limitations of this technique are considered in this work: firstly, th...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
We present new, general-purpose kernels for protein structure analysis, and describe how to apply them to structural motif discovery and function classification. Experiments show ...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
Kernel functions have become an extremely popular tool in machine learning, with an attractive theory as well. This theory views a kernel as implicitly mapping data points into a ...