Paper Abstract and Keywords |
Presentation |
2023-05-19 10:30
Privacy Preserving Deep Unrolling Methods using Random Unitary Transform Nichika Yuge, Takayuki Nakachi, Morikazu Nakamura (Univ. of the Ryukyus.) SIP2023-10 BioX2023-10 IE2023-10 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Edge and cloud computing has been spreading in many fields including machine learning.Sparse modeling attracts attention as machine learning works with a small amount of training data.However, edge and cloud computing poses some serious privacy issues for end users, such as unauthorized use, and data leaks.To address this issue, a privacy-preserving ISTA algorithm based on a random unitary transform has been proposed. which is one of the LASSO solutions for sparse modeling.This algorithm enables data analysis and signal processing while preserving privacy. LISTA and TISTA methods using deep unrolling have been developed, which provide significantly faster convergence than ISTA.
In this report, we propose secure LISTA and secure TISTA algorithms that incorporate privacy-preserving techniques based on a random unitary transform. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Sparse Modeling / LISTA / TISTA / Random Unitary Transform / Deep Unrolling / / / |
Reference Info. |
IEICE Tech. Rep., vol. 123, no. 27, SIP2023-10, pp. 41-46, May 2023. |
Paper # |
SIP2023-10 |
Date of Issue |
2023-05-11 (SIP, BioX, IE) |
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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SIP2023-10 BioX2023-10 IE2023-10 |
Conference Information |
Committee |
BioX SIP IE ITE-IST ITE-ME |
Conference Date |
2023-05-18 - 2023-05-19 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Sansui Hall, Mie University |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
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Paper Information |
Registration To |
SIP |
Conference Code |
2023-05-BioX-SIP-IE-IST-ME |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Privacy Preserving Deep Unrolling Methods using Random Unitary Transform |
Sub Title (in English) |
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Keyword(1) |
Sparse Modeling |
Keyword(2) |
LISTA |
Keyword(3) |
TISTA |
Keyword(4) |
Random Unitary Transform |
Keyword(5) |
Deep Unrolling |
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1st Author's Name |
Nichika Yuge |
1st Author's Affiliation |
University of the Ryukyus. (Univ. of the Ryukyus.) |
2nd Author's Name |
Takayuki Nakachi |
2nd Author's Affiliation |
University of the Ryukyus. (Univ. of the Ryukyus.) |
3rd Author's Name |
Morikazu Nakamura |
3rd Author's Affiliation |
University of the Ryukyus. (Univ. of the Ryukyus.) |
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Speaker |
Author-1 |
Date Time |
2023-05-19 10:30:00 |
Presentation Time |
30 minutes |
Registration for |
SIP |
Paper # |
SIP2023-10, BioX2023-10, IE2023-10 |
Volume (vol) |
vol.123 |
Number (no) |
no.27(SIP), no.28(BioX), no.29(IE) |
Page |
pp.41-46 |
#Pages |
6 |
Date of Issue |
2023-05-11 (SIP, BioX, IE) |
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