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Paper Abstract and Keywords
Presentation 2023-03-14 09:30
Dynamical analysis of concurrent and sequential multi-task learning in recurrent neural networks using the graph reduction method
Daichi Sugiyama, Hiroki Kurashige (Tokai Univ.) NC2022-99
Abstract (in Japanese) (See Japanese page) 
(in English) Humans and animals can learn multiple tasks. It is common that learning to learn tasks sequentially. However, it is not clear whether and how preceding learning affects subsequent one. Therefore, in this study, we investigated the difference in the dynamical features between the recurrent neural networks that learned multiple tasks concurrently and sequentially. Using the graph reduction method, we showed that there is no statistical difference between them. This result suggests that the sequentiality of learning does not make a difference for a particular class of tasks. It is necessary to extend this analysis to a wider range of task classes in the future.
Keyword (in Japanese) (See Japanese page) 
(in English) Recurrent neural networks / Multi-task learning / Graph reduction / / / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 425, NC2022-99, pp. 42-47, March 2023.
Paper # NC2022-99 
Date of Issue 2023-03-06 (NC) 
ISSN 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 NC MBE  
Conference Date 2023-03-13 - 2023-03-15 
Place (in Japanese) (See Japanese page) 
Place (in English) The Univ. of Electro-Communications 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Brain architecture, General 
Paper Information
Registration To NC 
Conference Code 2023-03-NC-MBE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Dynamical analysis of concurrent and sequential multi-task learning in recurrent neural networks using the graph reduction method 
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Keyword(1) Recurrent neural networks  
Keyword(2) Multi-task learning  
Keyword(3) Graph reduction  
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1st Author's Name Daichi Sugiyama  
1st Author's Affiliation Tokai University (Tokai Univ.)
2nd Author's Name Hiroki Kurashige  
2nd Author's Affiliation Tokai University (Tokai Univ.)
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Speaker Author-1 
Date Time 2023-03-14 09:30:00 
Presentation Time 25 minutes 
Registration for NC 
Paper # NC2022-99 
Volume (vol) vol.122 
Number (no) no.425 
Page pp.42-47 
#Pages
Date of Issue 2023-03-06 (NC) 


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