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Paper Abstract and Keywords
Presentation 2014-11-17 17:00
[Poster Presentation] Efficient leave-one-out cross-validation for L2-regularized classifier
Shota Okumura, Yoshiki Suzuki, Kohei Ogawa, Yuki Shinmura, Ichiro Takeuchi (NIT) IBISML2014-44
Abstract (in Japanese) (See Japanese page) 
(in English) Leave-one-out cross-validation (LOOCV) is a useful tool
for estimating generalization performances of
various machine learning algorithms.
However,
except for some special cases,
computing LOOCV error is quite time-consuming
because we must train as many models as the number of instances.
In this study,
we propose an efficient method
for LOOCV of $L_2$-regularized convex binary classification algorithms.
The proposed method allows us to make decisions on whether the left-out instance is correctly classified or not
before actually solving the optimization problem.
The proposed approach can be applicable to wider class of problems than existing approaches
and it can also be used as a stopping criterion in the optimization process.
We illustrate the advantage of the proposed method based on numerical experiments.
Keyword (in Japanese) (See Japanese page) 
(in English) cross-validation / convex optimization / model selection / support vector machine / / / /  
Reference Info. IEICE Tech. Rep., vol. 114, no. 306, IBISML2014-44, pp. 73-80, Nov. 2014.
Paper # IBISML2014-44 
Date of Issue 2014-11-10 (IBISML) 
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)
Download PDF IBISML2014-44

Conference Information
Committee IBISML  
Conference Date 2014-11-17 - 2014-11-19 
Place (in Japanese) (See Japanese page) 
Place (in English) Nagoya Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To IBISML 
Conference Code 2014-11-IBISML 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Efficient leave-one-out cross-validation for L2-regularized classifier 
Sub Title (in English)  
Keyword(1) cross-validation  
Keyword(2) convex optimization  
Keyword(3) model selection  
Keyword(4) support vector machine  
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Keyword(6)  
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1st Author's Name Shota Okumura  
1st Author's Affiliation Nagoya Institute of Technology (NIT)
2nd Author's Name Yoshiki Suzuki  
2nd Author's Affiliation Nagoya Institute of Technology (NIT)
3rd Author's Name Kohei Ogawa  
3rd Author's Affiliation Nagoya Institute of Technology (NIT)
4th Author's Name Yuki Shinmura  
4th Author's Affiliation Nagoya Institute of Technology (NIT)
5th Author's Name Ichiro Takeuchi  
5th Author's Affiliation Nagoya Institute of Technology (NIT)
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Speaker Author-1 
Date Time 2014-11-17 17:00:00 
Presentation Time 180 minutes 
Registration for IBISML 
Paper # IBISML2014-44 
Volume (vol) vol.114 
Number (no) no.306 
Page pp.73-80 
#Pages 8 
Date of Issue 2014-11-10 (IBISML) 

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