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Paper Abstract and Keywords
Presentation 2020-10-29 16:10
Numerical research on effects of quantization in SNN learned by backpropagation
Yumi Watanabe, Jun Ohkubo (Saitama Univ.) NC2020-14
Abstract (in Japanese) (See Japanese page) 
(in English) There are many studies to quantize the parameters of neural networks. For example, while there are methods of quantizing at the time of learning, there are also methods of quantizing learned parameters, which have advantages such as memory reduction and execution time reduction. In recent years, research on spiking neural networks (SNN) has been promoted by proposing approximation methods for the backpropagation. However, there is not much research on quantization. In this study, we numerically evaluate how the quantization of weights affects the performance after training the SNN learned by backpropagation.
Keyword (in Japanese) (See Japanese page) 
(in English) Quantization / Backpropagation / Neural Network / Spiking Neural Network(SNN) / / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 216, NC2020-14, pp. 29-33, Oct. 2020.
Paper # NC2020-14 
Date of Issue 2020-10-22 (NC) 
ISSN Print edition: ISSN 0913-5685  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 NC2020-14

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) Numerical research on effects of quantization in SNN learned by backpropagation 
Sub Title (in English)  
Keyword(1) Quantization  
Keyword(2) Backpropagation  
Keyword(3) Neural Network  
Keyword(4) Spiking Neural Network(SNN)  
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1st Author's Name Yumi Watanabe  
1st Author's Affiliation Saitama University (Saitama Univ.)
2nd Author's Name Jun Ohkubo  
2nd Author's Affiliation Saitama University (Saitama Univ.)
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Speaker
Date Time 2020-10-29 16:10:00 
Presentation Time 25 
Registration for NC 
Paper # IEICE-NC2020-14 
Volume (vol) IEICE-120 
Number (no) no.216 
Page pp.29-33 
#Pages IEICE-5 
Date of Issue IEICE-NC-2020-10-22 


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