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Paper Abstract and Keywords
Presentation 2017-11-10 13:00
Analysis of Dropout in online learning
Kazuyuki Hara (Nihon Univ.) IBISML2017-61
Abstract (in Japanese) (See Japanese page) 
(in English) Deep learning is the state-of-the-art in fields such as visual object recognition and speech recognition.
This learning uses a large number of layers and a huge number of units and connections. Therefore, overfitting is a serious problem with it, and the dropout which is a kind of regularization tool is used. However, in online learning,
the effect of dropout is not well known. This paper presents our investigation on the effect of dropout in online learning. We analyzed the effect of dropout on convergence speed near the singular point. Our results indicated
that dropout is effective in online learning. Dropout tends to avoid the singular point for convergence speed near that point.
Keyword (in Japanese) (See Japanese page) 
(in English) Deep Learning / Dropout / Slow dynamics / Multilayer perceptron / Teacher-Student formulation / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 293, IBISML2017-61, pp. 201-206, Nov. 2017.
Paper # IBISML2017-61 
Date of Issue 2017-11-02 (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. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
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Conference Information
Committee IBISML  
Conference Date 2017-11-08 - 2017-11-10 
Place (in Japanese) (See Japanese page) 
Place (in English) Univ. of Tokyo 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Information-Based Induction Science Workshop (IBIS2017) 
Paper Information
Registration To IBISML 
Conference Code 2017-11-IBISML 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Analysis of Dropout in online learning 
Sub Title (in English)  
Keyword(1) Deep Learning  
Keyword(2) Dropout  
Keyword(3) Slow dynamics  
Keyword(4) Multilayer perceptron  
Keyword(5) Teacher-Student formulation  
1st Author's Name Kazuyuki Hara  
1st Author's Affiliation Nihon University (Nihon Univ.)
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Date Time 2017-11-10 13:00:00 
Presentation Time 150 
Registration for IBISML 
Paper # IEICE-IBISML2017-61 
Volume (vol) IEICE-117 
Number (no) no.293 
Page pp.201-206 
#Pages IEICE-6 
Date of Issue IEICE-IBISML-2017-11-02 

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