1769 search results - page 37 / 354 » Prediction on Spike Data Using Kernel Algorithms |
ICPR
2008
IEEE
14 years 11 months ago
2008
IEEE
In this work we present a new string similarity feature, the sparse spatial sample (SSS). An SSS is a set of short substrings at specific spatial displacements contained in the or...
CIDM
2007
IEEE
14 years 2 months ago
2007
IEEE
Kernel methods are effective approaches to the modeling of structured objects in learning algorithms. Their major drawback is the typically high computational complexity of kernel ...
CIDM
2009
IEEE
14 years 2 months ago
2009
IEEE
The graph classification problem is learning to classify separate, individual graphs in a graph database into two or more categories. A number of algorithms have been introduced fo...
ICML
2007
IEEE
14 years 11 months ago
2007
IEEE
We address the problem of feature selection in a kernel space to select the most discriminative and informative features for classification and data analysis. This is a difficult ...
ICML
2005
IEEE
14 years 11 months ago
2005
IEEE
Semi-supervised clustering algorithms aim to improve clustering results using limited supervision. The supervision is generally given as pairwise constraints; such constraints are...