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Paper Abstract and Keywords
Presentation 2015-03-05 13:00
[Invited Talk] Detection of cheating in Boltzmann machine learning -- A parameter-free algorithm to sparse solution --
Masayuki Ohzeki (KU) IBISML2014-85
Abstract (in Japanese) (See Japanese page) 
(in English) We generalize a mathematical model in the item response theory into that in the Boltzmann machine learning to detect “cheating students”. The cheating students are hopefully expected to be rare under normal condition holding tests. (We strongly hope!) In other words, the cheating students are expected to be sparse. In the present study, we employ a greedy algorithm, the decimation algorithm, which is free from the arbitrary coefficient. We confirmed that, when the sparseness is strong, the decimation algorithm outperforms the L1 regularization and establish a basic technique to detect the cheating students.
Keyword (in Japanese) (See Japanese page) 
(in English) Boltzmann machine learning / Item response theory / sparseness / greedy algorithm / / / /  
Reference Info. IEICE Tech. Rep., vol. 114, no. 502, IBISML2014-85, pp. 1-8, March 2015.
Paper # IBISML2014-85 
Date of Issue 2015-02-26 (IBISML) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
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. (No. 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
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Conference Information
Committee IBISML  
Conference Date 2015-03-05 - 2015-03-06 
Place (in Japanese) (See Japanese page) 
Place (in English) Kyoto University 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Statistical mathematics, machine learning, data mining, and others 
Paper Information
Registration To IBISML 
Conference Code 2015-03-IBISML 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Detection of cheating in Boltzmann machine learning 
Sub Title (in English) A parameter-free algorithm to sparse solution 
Keyword(1) Boltzmann machine learning  
Keyword(2) Item response theory  
Keyword(3) sparseness  
Keyword(4) greedy algorithm  
1st Author's Name Masayuki Ohzeki  
1st Author's Affiliation Kyoto University (KU)
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Date Time 2015-03-05 13:00:00 
Presentation Time 60 
Registration for IBISML 
Paper # IEICE-IBISML2014-85 
Volume (vol) IEICE-114 
Number (no) no.502 
Page pp.1-8 
#Pages IEICE-8 
Date of Issue IEICE-IBISML-2015-02-26 

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