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Paper Abstract and Keywords
Presentation 2020-10-30 10:50
statistical mechanical analysis of catastrophic forgetting in continual learning with teacher and student networks
Haruka Asanuma, Shiro Takagi, Yoshihiro Nagano, Yuki Yoshida (Tokyo Univ.), Yasuhiko Igarashi (Tsukuba Univ.), Masato Okada (Tokyo Univ.) NC2020-18
Abstract (in Japanese) (See Japanese page) 
(in English) When single neural networks sequentially learns more than one task, catastrophic forgetting occurs except for the last task.
It is empirically known from previous studies that the input space similarity and the task-to-task similarity are important factors that govern catastrophic forgetting.
While the method to avoid catastrophic forgetting has been studied, it is not clear how each factor specifically affects catastrophic forgetting as no consensus on a framework has been established to discuss catastrophic forgetting in a unified manner.
In this study, we modeled and analyzed a solvable model of single-layer linear neural networks of continual learning that incorporates input space similarity and task-to-task similarity using teacher and student learning and statistical mechanics formulation.
As a result of analysis, we found that the input space similarity and task-to-task similarity affect the catastrophic forgetting by multiplication.
Keyword (in Japanese) (See Japanese page) 
(in English) catastrophic forgetting / a single-layer linear model / a regression problem / online learning / teacher and student learning / statistical mechanical analysis / generalization error /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 216, NC2020-18, pp. 50-55, Oct. 2020.
Paper # NC2020-18 
Date of Issue 2020-10-22 (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)
Download PDF NC2020-18

Conference Information
Committee MBE NC NLP CAS  
Conference Date 2020-10-29 - 2020-10-30 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) ME，NC，CAS，NLP 
Paper Information
Registration To NC 
Conference Code 2020-10-MBE-NC-NLP-CAS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) statistical mechanical analysis of catastrophic forgetting in continual learning with teacher and student networks 
Sub Title (in English)  
Keyword(1) catastrophic forgetting  
Keyword(2) a single-layer linear model  
Keyword(3) a regression problem  
Keyword(4) online learning  
Keyword(5) teacher and student learning  
Keyword(6) statistical mechanical analysis  
Keyword(7) generalization error  
Keyword(8)  
1st Author's Name Haruka Asanuma  
1st Author's Affiliation Tokyo University (Tokyo Univ.)
2nd Author's Name Shiro Takagi  
2nd Author's Affiliation Tokyo University (Tokyo Univ.)
3rd Author's Name Yoshihiro Nagano  
3rd Author's Affiliation Tokyo University (Tokyo Univ.)
4th Author's Name Yuki Yoshida  
4th Author's Affiliation Tokyo University (Tokyo Univ.)
5th Author's Name Yasuhiko Igarashi  
5th Author's Affiliation University of Tsukuba (Tsukuba Univ.)
6th Author's Name Masato Okada  
6th Author's Affiliation Tokyo University (Tokyo Univ.)
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Speaker Author-1 
Date Time 2020-10-30 10:50:00 
Presentation Time 25 minutes 
Registration for NC 
Paper # NC2020-18 
Volume (vol) vol.120 
Number (no) no.216 
Page pp.50-55 
#Pages 6 
Date of Issue 2020-10-22 (NC) 

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