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Paper Abstract and Keywords
Presentation 2007-03-14 10:40
Optimization of the support vector machine's kernels using a feedforward neural network
Shin'ichi Tamura (DENSO CORP.)
Abstract (in Japanese) (See Japanese page) 
(in English) A novel approach to determining the optimal kernel parameters of Support Vector Machines is proposed. Based on the fact that a feed-forward neural network with infinitely many hidden units can realize any continuous mapping, an optimal mapping from the input space to a higher-dimensional space is estimated by neural network learning with a given learning input-output data. The kernel parameters of Support Vector Machines is determined using the criterion that the mapping determined implicitly by the kernel be as close as possible to the estimated mapping of a feed-forward neural network.
Keyword (in Japanese) (See Japanese page) 
(in English) Feedforward neural network / Support Vector Machine / Kernel / / / / /  
Reference Info. IEICE Tech. Rep., vol. 106, no. 588, NC2006-137, pp. 115-120, March 2007.
Paper # NC2006-137 
Date of Issue 2007-03-07 (NC) 
ISSN Print edition: ISSN 0913-5685
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Conference Information
Committee NC  
Conference Date 2007-03-14 - 2007-03-16 
Place (in Japanese) (See Japanese page) 
Place (in English) Tamagawa University 
Topics (in Japanese) (See Japanese page) 
Topics (in English) General 
Paper Information
Registration To NC 
Conference Code 2007-03-NC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Optimization of the support vector machine's kernels using a feedforward neural network 
Sub Title (in English)  
Keyword(1) Feedforward neural network  
Keyword(2) Support Vector Machine  
Keyword(3) Kernel  
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1st Author's Name Shin'ichi Tamura  
1st Author's Affiliation DENSO CORPORATION (DENSO CORP.)
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Speaker Author-1 
Date Time 2007-03-14 10:40:00 
Presentation Time 20 minutes 
Registration for NC 
Paper # NC2006-137 
Volume (vol) vol.106 
Number (no) no.588 
Page pp.115-120 
#Pages
Date of Issue 2007-03-07 (NC) 


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