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Paper Abstract and Keywords
Presentation 2024-03-13 15:05
Efficient Replay Data Selection in Continual Federated Learning Model
Yuto Kitano (Kobe Univ), Lihua Wang (NICT), Seiichi Ozawa (Kobe Univ) IT2023-96 ISEC2023-95 WBS2023-84 RCC2023-78
Abstract (in Japanese) (See Japanese page) 
(in English) In this study, we propose a continual federated learning that can continuously learn distributed data generated daily by multiple organizations to maintain high performance. Specifically, we propose a method for efficiently selecting a dataset for replay from past training data to achieve high-performance continual learning and incorporate it into eFL-Boost, a federated learning for gradient boosting decision tree model proposed by Yamamoto et al. This enables robust prediction even for non-stationary data by communicating only statistical information with a low risk of information leakage between organizations and selecting optimal data for replay.
Keyword (in Japanese) (See Japanese page) 
(in English) Continual learning / federated learning / privacy preservation / gradient boosting decision tree / / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 424, ISEC2023-95, pp. 135-141, March 2024.
Paper # ISEC2023-95 
Date of Issue 2024-03-06 (IT, ISEC, WBS, RCC) 
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 IT2023-96 ISEC2023-95 WBS2023-84 RCC2023-78

Conference Information
Committee RCC ISEC IT WBS  
Conference Date 2024-03-13 - 2024-03-14 
Place (in Japanese) (See Japanese page) 
Place (in English) Osaka Univ. (Suita Campus) 
Topics (in Japanese) (See Japanese page) 
Topics (in English) RCC, ISEC, IT, WBS 
Paper Information
Registration To ISEC 
Conference Code 2024-03-RCC-ISEC-IT-WBS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Efficient Replay Data Selection in Continual Federated Learning Model 
Sub Title (in English)  
Keyword(1) Continual learning  
Keyword(2) federated learning  
Keyword(3) privacy preservation  
Keyword(4) gradient boosting decision tree  
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1st Author's Name Yuto Kitano  
1st Author's Affiliation Kobe University (Kobe Univ)
2nd Author's Name Lihua Wang  
2nd Author's Affiliation National Institute of Information and Communications Technology (NICT)
3rd Author's Name Seiichi Ozawa  
3rd Author's Affiliation Kobe University (Kobe Univ)
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Speaker Author-1 
Date Time 2024-03-13 15:05:00 
Presentation Time 25 minutes 
Registration for ISEC 
Paper # IT2023-96, ISEC2023-95, WBS2023-84, RCC2023-78 
Volume (vol) vol.123 
Number (no) no.423(IT), no.424(ISEC), no.425(WBS), no.426(RCC) 
Page pp.135-141 
#Pages
Date of Issue 2024-03-06 (IT, ISEC, WBS, RCC) 


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