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Paper Abstract and Keywords
Presentation 2014-01-23 10:30
Multi-Class Support Vector Machine based on Minimum Classification Error Criterion
Hisashi Uehara (Doshisha Univ.), Hideyuki Watanabe (NICT), Shigeru Katagiri, Miho Ohsaki (Doshisha Univ.), Shigeki Matsuda, Chiori Hori (NICT) PRMU2013-93 MVE2013-34
Abstract (in Japanese) (See Japanese page) 
(in English) Gradient-descent-based optimization methods used in Minimum Classification Error (MCE) training are not necessarily easily-handled, because they often require careful devices to minimize the non-convex objective of MCE training. To alleviate this difficulty, we propose in this paper a new training method by applying the optimization method of Multi-class Support Vector Machine, which runs fast and does not need know-how, to the MCE method. This application is realized by replacing the non-convex objective of MCE training with a new auxiliary function that is easy to optimize. The paper introduces the definition of proposed method in detail and it briefly reports experimental evaluation results for the proposed method.
Keyword (in Japanese) (See Japanese page) 
(in English) Minimum classification error training / Multi-class support vector machine / Auxiliary function method / Kernel / / / /  
Reference Info. IEICE Tech. Rep., vol. 113, no. 402, PRMU2013-93, pp. 13-18, Jan. 2014.
Paper # PRMU2013-93 
Date of Issue 2014-01-16 (PRMU, MVE) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
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Conference Information
Committee PRMU IPSJ-CVIM MVE  
Conference Date 2014-01-23 - 2014-01-24 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To PRMU 
Conference Code 2014-01-PRMU-CVIM-MVE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Multi-Class Support Vector Machine based on Minimum Classification Error Criterion 
Sub Title (in English)  
Keyword(1) Minimum classification error training  
Keyword(2) Multi-class support vector machine  
Keyword(3) Auxiliary function method  
Keyword(4) Kernel  
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1st Author's Name Hisashi Uehara  
1st Author's Affiliation Doshisha University (Doshisha Univ.)
2nd Author's Name Hideyuki Watanabe  
2nd Author's Affiliation National Institute of Information and Communications Technology (NICT)
3rd Author's Name Shigeru Katagiri  
3rd Author's Affiliation Doshisha University (Doshisha Univ.)
4th Author's Name Miho Ohsaki  
4th Author's Affiliation Doshisha University (Doshisha Univ.)
5th Author's Name Shigeki Matsuda  
5th Author's Affiliation National Institute of Information and Communications Technology (NICT)
6th Author's Name Chiori Hori  
6th Author's Affiliation National Institute of Information and Communications Technology (NICT)
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Speaker Author-1 
Date Time 2014-01-23 10:30:00 
Presentation Time 30 minutes 
Registration for PRMU 
Paper # PRMU2013-93, MVE2013-34 
Volume (vol) vol.113 
Number (no) no.402(PRMU), no.403(MVE) 
Page pp.13-18 
#Pages 6 
Date of Issue 2014-01-16 (PRMU, MVE) 

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