133 search results - page 2 / 27 » Margin and Radius Based Multiple Kernel Learning |
ICANN
2005
Springer
13 years 11 months ago
2005
Springer
Abstract. Tuning hyper-parameters is a necessary step to improve learning algorithm performances. For Support Vector Machine classifiers, adjusting kernel parameters increases dra...
AAAI
2012
11 years 8 months ago
2012
Selecting the optimal kernel is an important and difficult challenge in applying kernel methods to pattern recognition. To address this challenge, multiple kernel learning (MKL) ...
ICML
2003
IEEE
14 years 6 months ago
2003
IEEE
A new kernel function between two labeled graphs is presented. Feature vectors are defined as the counts of label paths produced by random walks on graphs. The kernel computation ...
PAMI
2010
13 years 4 months ago
2010
—Adapting the hyperparameters of support vector machines (SVMs) is a challenging model selection problem, especially when flexible kernels are to be adapted and data are scarce....
GECCO
2006
Springer
13 years 9 months ago
2006
Springer
In this paper we embed evolutionary computation into statistical learning theory. First, we outline the connection between large margin optimization and statistical learning and s...