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Paper Abstract and Keywords
Presentation 2021-03-05 14:30
Adaptive Optimization Method in Artificial Neural Network that Independ on Learning Rate
Tetsuya Sato, Yukari Yamauti (Nihon Univ.) NC2020-72
Abstract (in Japanese) (See Japanese page) 
(in English) What kind of optimizer is used in machine learning is an important issue. SGD has high accuracy but slow convergence and is not stable. Therefore, optimizers like Adam, which converges quickly and is stable, has been studied. However, Adam is not as accurate as SGD and is as sensitive to learning rate settings as SGD. Therefore, in this study we propose a method that combines multiple optimizer and has high accuracy and quick convergence without depending on learning rate. As a result of the experiment, the proposed method can achieve high accuracy regardless of size on learning rate.
Keyword (in Japanese) (See Japanese page) 
(in English) Optimizer / Adaptive Learning Rate / Adam / RAdam / AdaBound / AdaBelief / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 403, NC2020-72, pp. 169-173, March 2021.
Paper # NC2020-72 
Date of Issue 2021-02-24 (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 NC2020-72

Conference Information
Committee NC MBE  
Conference Date 2021-03-03 - 2021-03-05 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Neuro Computing, Medical Engineering, etc. 
Paper Information
Registration To NC 
Conference Code 2021-03-NC-MBE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Adaptive Optimization Method in Artificial Neural Network that Independ on Learning Rate 
Sub Title (in English)  
Keyword(1) Optimizer  
Keyword(2) Adaptive Learning Rate  
Keyword(3) Adam  
Keyword(4) RAdam  
Keyword(5) AdaBound  
Keyword(6) AdaBelief  
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Keyword(8)  
1st Author's Name Tetsuya Sato  
1st Author's Affiliation Nihon University (Nihon Univ.)
2nd Author's Name Yukari Yamauti  
2nd Author's Affiliation Nihon University (Nihon Univ.)
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Speaker Author-1 
Date Time 2021-03-05 14:30:00 
Presentation Time 25 minutes 
Registration for NC 
Paper # NC2020-72 
Volume (vol) vol.120 
Number (no) no.403 
Page pp.169-173 
#Pages 5 
Date of Issue 2021-02-24 (NC) 

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