Paper Abstract and Keywords |
Presentation |
2022-03-04 15:55
Federated Learning with Correlated Sensing Data in Wireless Networks Keita Hibari, Masaya Kambara, Tomotaka Kimura, Jun Cheng (Doshisha Univ) CAS2021-99 CS2021-101 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Federated leaning in wireless networks is considered where devices are gathered in several locations and the sensing data of the devices in each location are correlated. A device which wants to participate in the training sends a reservation signal to the server at its randomly assigned slot, and devices which detect the signal will not participate in the training. As a result, both of the amount of training computation in the systems and communication traffic between devices and the server are reduced. Simulations show that the recognition accuracy of MINST dataset with the proposed training method has no much degradation, compared with the all-device training. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Correlated sensing data / Autonomous device selection / Neural networks / Wireless federated learning / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 121, no. 395, CS2021-101, pp. 136-140, March 2022. |
Paper # |
CS2021-101 |
Date of Issue |
2022-02-24 (CAS, CS) |
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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CAS2021-99 CS2021-101 |
Conference Information |
Committee |
CAS CS |
Conference Date |
2022-03-03 - 2022-03-04 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Online |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Network processor, Signal processing and circuits for communications, Wireless LAN / PAN, etc. |
Paper Information |
Registration To |
CS |
Conference Code |
2022-03-CAS-CS |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Federated Learning with Correlated Sensing Data in Wireless Networks |
Sub Title (in English) |
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Correlated sensing data |
Keyword(2) |
Autonomous device selection |
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Neural networks |
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Wireless federated learning |
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1st Author's Name |
Keita Hibari |
1st Author's Affiliation |
Doshisha University (Doshisha Univ) |
2nd Author's Name |
Masaya Kambara |
2nd Author's Affiliation |
Doshisha University (Doshisha Univ) |
3rd Author's Name |
Tomotaka Kimura |
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Doshisha University (Doshisha Univ) |
4th Author's Name |
Jun Cheng |
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Doshisha University (Doshisha Univ) |
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Speaker |
Author-1 |
Date Time |
2022-03-04 15:55:00 |
Presentation Time |
25 minutes |
Registration for |
CS |
Paper # |
CAS2021-99, CS2021-101 |
Volume (vol) |
vol.121 |
Number (no) |
no.394(CAS), no.395(CS) |
Page |
pp.136-140 |
#Pages |
5 |
Date of Issue |
2022-02-24 (CAS, CS) |
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