| Paper Abstract and Keywords |
| Presentation |
2022-11-18 13:05
An Analysis of Model Parameters Propagation over Decentralized Federated Learning Koshi Eguchi, Hideya Ochiai, Hiroshi Esaki (Univ. Tokyo) CAS2022-51 MSS2022-34 |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
Although there have been many studies on Decentralized Federated Learning (DFL), few have focused on the propagation of learning results among terminal nodes. In this study, we analyzed how the learning results of each node are propagated to other nodes in DFL by changing the connection configuration of nodes, learning models, and model aggregation coefficients. By doing so, we aim to elucidate how the learning results of one node are propagated to other nodes, so that DFL can be used more efficiently. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
Decentralized Federated Learning / Model Parameters / Non-IID data / / / / / |
| Reference Info. |
IEICE Tech. Rep., vol. 122, no. 254, MSS2022-34, pp. 67-70, Nov. 2022. |
| Paper # |
MSS2022-34 |
| Date of Issue |
2022-11-10 (CAS, MSS) |
| 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 |
CAS2022-51 MSS2022-34 |
| Conference Information |
| Committee |
CAS MSS IPSJ-AL |
| Conference Date |
2022-11-17 - 2022-11-18 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
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| Topics (in Japanese) |
(See Japanese page) |
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| Paper Information |
| Registration To |
MSS |
| Conference Code |
2022-11-CAS-MSS-AL |
| Language |
Japanese |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
An Analysis of Model Parameters Propagation over Decentralized Federated Learning |
| Sub Title (in English) |
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| Keyword(1) |
Decentralized Federated Learning |
| Keyword(2) |
Model Parameters |
| Keyword(3) |
Non-IID data |
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| 1st Author's Name |
Koshi Eguchi |
| 1st Author's Affiliation |
The University of Tokyo (Univ. Tokyo) |
| 2nd Author's Name |
Hideya Ochiai |
| 2nd Author's Affiliation |
The University of Tokyo (Univ. Tokyo) |
| 3rd Author's Name |
Hiroshi Esaki |
| 3rd Author's Affiliation |
The University of Tokyo (Univ. Tokyo) |
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| Speaker |
Author-1 |
| Date Time |
2022-11-18 13:05:00 |
| Presentation Time |
20 minutes |
| Registration for |
MSS |
| Paper # |
CAS2022-51, MSS2022-34 |
| Volume (vol) |
vol.122 |
| Number (no) |
no.253(CAS), no.254(MSS) |
| Page |
pp.67-70 |
| #Pages |
4 |
| Date of Issue |
2022-11-10 (CAS, MSS) |