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Paper Abstract and Keywords
Presentation 2024-06-20 15:50
Distributionally Robust Safe Sample Screening and Its Application to Infinite-width Deep Neural Networks
Tatsuya Aoyama (Nagoya Univ.), Hiroyuki Hanada (RIKEN), Satoshi Akahane, Yoshito Okura, Tomonari Tanaka (Nagoya Univ.), Yu Inatsu (NITech), Noriaki Hashimoto (RIKEN), Taro Murayama, Lee Hanju, Shinya Kojima (DENSO), Ichiro Takeuchi (Nagoya Univ.) NC2024-10 IBISML2024-10
Abstract (in Japanese) (See Japanese page) 
(in English) In machine learning, handling large datasets has been problematic in computational resources. For this issue, safe sample screening (SSS) is an effective solution to remove unnecessary samples before the optimization computation. However, conventional SSS cannot be applied under covariate shift, where the input data distribution changes. In this study, we propose a safe sample screening method that robustly removes unnecessary samples against distribution changes, mainly targeting support vector machines (SVM). Finally we experimentally demonstrate its validity for an infinite-width deep neural network.
Keyword (in Japanese) (See Japanese page) 
(in English) Safe Sample Screening / Distributionally Robust / Support Vector Machine / Infinite-width Deep Neural Networks / / / /  
Reference Info. IEICE Tech. Rep., vol. 124, no. 86, IBISML2024-10, pp. 67-72, June 2024.
Paper # IBISML2024-10 
Date of Issue 2024-06-13 (NC, IBISML) 
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 NC2024-10 IBISML2024-10

Conference Information
Committee IBISML NC IPSJ-BIO IPSJ-MPS  
Conference Date 2024-06-20 - 2024-06-22 
Place (in Japanese) (See Japanese page) 
Place (in English) OIST 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To IBISML 
Conference Code 2024-06-IBISML-NC-BIO-MPS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Distributionally Robust Safe Sample Screening and Its Application to Infinite-width Deep Neural Networks 
Sub Title (in English)  
Keyword(1) Safe Sample Screening  
Keyword(2) Distributionally Robust  
Keyword(3) Support Vector Machine  
Keyword(4) Infinite-width Deep Neural Networks  
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1st Author's Name Tatsuya Aoyama  
1st Author's Affiliation Nagoya University (Nagoya Univ.)
2nd Author's Name Hiroyuki Hanada  
2nd Author's Affiliation RIKEN (RIKEN)
3rd Author's Name Satoshi Akahane  
3rd Author's Affiliation Nagoya University (Nagoya Univ.)
4th Author's Name Yoshito Okura  
4th Author's Affiliation Nagoya University (Nagoya Univ.)
5th Author's Name Tomonari Tanaka  
5th Author's Affiliation Nagoya University (Nagoya Univ.)
6th Author's Name Yu Inatsu  
6th Author's Affiliation Nagoya Institute of Technology (NITech)
7th Author's Name Noriaki Hashimoto  
7th Author's Affiliation RIKEN (RIKEN)
8th Author's Name Taro Murayama  
8th Author's Affiliation DENSO CORPORATION (DENSO)
9th Author's Name Lee Hanju  
9th Author's Affiliation DENSO CORPORATION (DENSO)
10th Author's Name Shinya Kojima  
10th Author's Affiliation DENSO CORPORATION (DENSO)
11th Author's Name Ichiro Takeuchi  
11th Author's Affiliation Nagoya University (Nagoya Univ.)
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Speaker Author-1 
Date Time 2024-06-20 15:50:00 
Presentation Time 25 minutes 
Registration for IBISML 
Paper # NC2024-10, IBISML2024-10 
Volume (vol) vol.124 
Number (no) no.85(NC), no.86(IBISML) 
Page pp.67-72 
#Pages 6 
Date of Issue 2024-06-13 (NC, IBISML) 

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