Multiple Kernel Learning Using Regularized Ho-Kashyap Classifier in Empirical Kernel Mapping Space

Author(s):  
Bo Yang ◽  
Yingyong Bu
2013 ◽  
Vol 333-335 ◽  
pp. 1406-1409
Author(s):  
Bo Yang

Different from the existing multiple kernel methods which mainly work in implicit kernel space, we propose a novel multiple kernel method in empirical kernel mapping space. In empirical kernel mapping space, the combination of kernels can be treated as the weighted fusion of empirical kernel mapping samples. Based this fact, we developed a multiple kernel Fisher method to realize multiple kernel classification in empirical kernel mapping space. The experiments here illustrate that the proposed multiple kernel fisher method is feasible and effective.


Author(s):  
Guo ◽  
Xiaoqian Zhang ◽  
Zhigui Liu ◽  
Xuqian Xue ◽  
Qian Wang ◽  
...  

Author(s):  
Andrew D. O'Harney ◽  
Andre Marquand ◽  
Katya Rubia ◽  
Kaylita Chantiluke ◽  
Anna Smith ◽  
...  

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