Paper Abstract and Keywords |
Presentation |
2022-11-24 15:45
A Study on Distributed Machine Learning with Rich Devices Feedbacking Results to Edge Servers Saki Takano (Ochanomizu Univ.), Akihiro Nakao (The Univ. of Tokyo), Saneyasu Yamaguchi (Kogakuin Univ.), Masato Oguchi (Ochanomizu Univ.) NS2022-111 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Many recent studies have focused on using the data collected by edge devices for machine learning by aggregating those data to a high-performance server. However, users may refuse to pass on their personal information to an external server owing to the risk of information leakage. To address this concern, we propose a distributed machine learning model in which the results trained on an edge server are inherited by edge devices, and only results authorized by the user are aggregated at the edge server. Experiments using the Jetson Nano as an edge device confirm that it can achieve better accuracy for both edge devices and the edge server while protecting privacy. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Edge Computing / Distributed Machine Learning / Federated Learning / Internet of Things / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 122, no. 274, NS2022-111, pp. 65-70, Nov. 2022. |
Paper # |
NS2022-111 |
Date of Issue |
2022-11-17 (NS) |
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 |
NS2022-111 |
Conference Information |
Committee |
NS ICM CQ NV |
Conference Date |
2022-11-24 - 2022-11-25 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Humanities and Social Sciences Center, Fukuoka Univ. + Online |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Network quality, Network measurement/management, Network virtualization, Network service, Blockchain, Security, Network intelligence/AI, etc. |
Paper Information |
Registration To |
NS |
Conference Code |
2022-11-NS-ICM-CQ-NV |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
A Study on Distributed Machine Learning with Rich Devices Feedbacking Results to Edge Servers |
Sub Title (in English) |
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Keyword(1) |
Edge Computing |
Keyword(2) |
Distributed Machine Learning |
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Federated Learning |
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Internet of Things |
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1st Author's Name |
Saki Takano |
1st Author's Affiliation |
Ochanomizu University (Ochanomizu Univ.) |
2nd Author's Name |
Akihiro Nakao |
2nd Author's Affiliation |
The University of Tokyo (The Univ. of Tokyo) |
3rd Author's Name |
Saneyasu Yamaguchi |
3rd Author's Affiliation |
Kogakuin University (Kogakuin Univ.) |
4th Author's Name |
Masato Oguchi |
4th Author's Affiliation |
Ochanomizu University (Ochanomizu Univ.) |
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Speaker |
Author-1 |
Date Time |
2022-11-24 15:45:00 |
Presentation Time |
25 minutes |
Registration for |
NS |
Paper # |
NS2022-111 |
Volume (vol) |
vol.122 |
Number (no) |
no.274 |
Page |
pp.65-70 |
#Pages |
6 |
Date of Issue |
2022-11-17 (NS) |
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