IEICE Technical Committee Submission System
Conference Paper's Information
Online Proceedings
[Sign in]
Tech. Rep. Archives
 Go Top Page Go Previous   [Japanese] / [English] 

Paper Abstract and Keywords
Presentation 2022-06-27 14:50
AI knowledge forgetting based on the importance of model parameters
Tomoya Yamashita, Masanori Yamada (NTT) NC2022-3 IBISML2022-3
Abstract (in Japanese) (See Japanese page) 
(in English) The accuracy of Deep Learning has been greatly improved by the progress of research in computer technology and Deep Learning techniques, and it has produced results in many fields. However, as Deep Learning becomes more widely used, problems related to privacy violation and data leakage are expected to arise. In this paper, we aim to solve these problems by making Deep Learning models forget their knowledge. We propose a method of forgetting knowledge about a desired task by adding noise to Deep Learning model parameters. Experimental results confirm that the proposed method achieves knowledge oblivion of Deep Learning models.
Keyword (in Japanese) (See Japanese page) 
(in English) Deep Learning / Continual Learning / EWC / Catastrophic Forgetting / Privacy Protection / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 90, IBISML2022-3, pp. 14-19, June 2022.
Paper # IBISML2022-3 
Date of Issue 2022-06-20 (NC, IBISML) 
ISSN 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)
Download PDF NC2022-3 IBISML2022-3

Conference Information
Conference Date 2022-06-27 - 2022-06-29 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To IBISML 
Conference Code 2022-06-NC-IBISML-BIO-MPS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) AI knowledge forgetting based on the importance of model parameters 
Sub Title (in English)  
Keyword(1) Deep Learning  
Keyword(2) Continual Learning  
Keyword(3) EWC  
Keyword(4) Catastrophic Forgetting  
Keyword(5) Privacy Protection  
1st Author's Name Tomoya Yamashita  
1st Author's Affiliation NTT Social Informatics Laboratories (NTT)
2nd Author's Name Masanori Yamada  
2nd Author's Affiliation NTT Social Informatics Laboratories (NTT)
3rd Author's Name  
3rd Author's Affiliation ()
4th Author's Name  
4th Author's Affiliation ()
5th Author's Name  
5th Author's Affiliation ()
6th Author's Name  
6th Author's Affiliation ()
7th Author's Name  
7th Author's Affiliation ()
8th Author's Name  
8th Author's Affiliation ()
9th Author's Name  
9th Author's Affiliation ()
10th Author's Name  
10th Author's Affiliation ()
11th Author's Name  
11th Author's Affiliation ()
12th Author's Name  
12th Author's Affiliation ()
13th Author's Name  
13th Author's Affiliation ()
14th Author's Name  
14th Author's Affiliation ()
15th Author's Name  
15th Author's Affiliation ()
16th Author's Name  
16th Author's Affiliation ()
17th Author's Name  
17th Author's Affiliation ()
18th Author's Name  
18th Author's Affiliation ()
19th Author's Name  
19th Author's Affiliation ()
20th Author's Name  
20th Author's Affiliation ()
Speaker Author-1 
Date Time 2022-06-27 14:50:00 
Presentation Time 25 minutes 
Registration for IBISML 
Paper # NC2022-3, IBISML2022-3 
Volume (vol) vol.122 
Number (no) no.89(NC), no.90(IBISML) 
Page pp.14-19 
Date of Issue 2022-06-20 (NC, IBISML) 

[Return to Top Page]

[Return to IEICE Web Page]

The Institute of Electronics, Information and Communication Engineers (IEICE), Japan