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 |
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) |
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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) |
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Quantization |
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Backpropagation |
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Neural Network |
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Spiking Neural Network(SNN) |
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1st Author's Name |
Yumi Watanabe |
1st Author's Affiliation |
Saitama University (Saitama Univ.) |
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Jun Ohkubo |
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Saitama University (Saitama Univ.) |
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Speaker |
Author-1 |
Date Time |
2020-10-29 16:10:00 |
Presentation Time |
25 minutes |
Registration for |
NC |
Paper # |
NC2020-14 |
Volume (vol) |
vol.120 |
Number (no) |
no.216 |
Page |
pp.29-33 |
#Pages |
5 |
Date of Issue |
2020-10-22 (NC) |
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