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Paper Abstract and Keywords
Presentation 2014-01-23 10:00
Minimum Classification Error Training with Automatic Control of Loss Smoothness
Hideaki Tanaka (Doshisha Univ.), Hideyuki Watanabe (NICT), Shigeru Katagiri, Miho Ohsaki (Doshisha Univ.), Shigeki Matsuda, Chiori Hori (NICT) PRMU2013-92 MVE2013-33
Abstract (in Japanese) (See Japanese page) 
(in English) The Minimum Classification Error (MCE) training has been successfully applied to various types of classifiers. However, its training power was casted only to the optimization of class boundaries in an original sample space. There is the possibility of applying the MCE training to some other features or feature space, which may lead to more accurate classification. Motivated by this, we introduce in this paper a new MCE training method, called Kernel Minimum Classification Error training. This new method is formalized by applying an MCE training associated with auxiliary-function-based optimization to a classifier that has linear discriminant functions and kernel feature projection. The formalization of the method is characterized by the use of cross-entropy loss as an auxiliary function. We also show basic performances of the method through several evaluation experiments.
Keyword (in Japanese) (See Japanese page) 
(in English) Minimum classification error training / Kernel method / Auxiliary function method / / / / /  
Reference Info. IEICE Tech. Rep., vol. 113, no. 402, PRMU2013-92, pp. 7-12, Jan. 2014.
Paper # PRMU2013-92 
Date of Issue 2014-01-16 (PRMU, MVE) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
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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) Minimum Classification Error Training with Automatic Control of Loss Smoothness 
Sub Title (in English)  
Keyword(1) Minimum classification error training  
Keyword(2) Kernel method  
Keyword(3) Auxiliary function method  
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1st Author's Name Hideaki Tanaka  
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 10:00:00 
Presentation Time 30 minutes 
Registration for PRMU 
Paper # PRMU2013-92, MVE2013-33 
Volume (vol) vol.113 
Number (no) no.402(PRMU), no.403(MVE) 
Page pp.7-12 
#Pages 6 
Date of Issue 2014-01-16 (PRMU, MVE) 

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