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Paper Abstract and Keywords
Presentation 2026-05-21 14:50
Low-Complexity and High-Accuracy Signal Recovery via SPSA-Based Step-Size Learning for ISTA
Masaki Kobayashi, Ayano Nakai-Kasai (NITech), Lantian Wei (TTI), Tadashi Wadayama (NITech) IT2026-5 EMM2026-5
Abstract (in Japanese) (See Japanese page) 
(in English) Compressed sensing enables signal recovery from a small number of measurements when the signal is sparse. ISTA (Iterative Shrinkage Thresholding Algorithm) is a well-known algorithm for solving the LASSO problem. However, its performance significantly depends on the choice of step-size parameters. Recently, deep unfolding methods have achieved high reconstruction accuracy, but they require expensive backpropagation training. In this paper, we propose SPSA-ISTA, which optimizes the step size of ISTA using SPSA (Simultaneous Perturbation Stochastic Approximation). The proposed method does not accurate gradient computation and enables efficient parameter optimization. Experimental results show that SPSA-ISTA improves reconstruction performance compared with conventional ISTA.
Keyword (in Japanese) (See Japanese page) 
(in English) Compressed sensing / ISTA / SPSA / deep unfolding / / / /  
Reference Info. IEICE Tech. Rep., vol. 126, no. 29, IT2026-5, pp. 24-29, May 2026.
Paper # IT2026-5 
Date of Issue 2026-05-14 (IT, EMM) 
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 IT2026-5 EMM2026-5

Conference Information
Committee IT EMM  
Conference Date 2026-05-21 - 2026-05-22 
Place (in Japanese) (See Japanese page) 
Place (in English) Kyoto Terrsa 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Information Security, Information Theory, Information Hiding, etc., Freshman session 
Paper Information
Registration To IT 
Conference Code 2026-05-IT-EMM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Low-Complexity and High-Accuracy Signal Recovery via SPSA-Based Step-Size Learning for ISTA 
Sub Title (in English)  
Keyword(1) Compressed sensing  
Keyword(2) ISTA  
Keyword(3) SPSA  
Keyword(4) deep unfolding  
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Keyword(6)  
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1st Author's Name Masaki Kobayashi  
1st Author's Affiliation Nagoya Institute of Technology (NITech)
2nd Author's Name Ayano Nakai-Kasai  
2nd Author's Affiliation Nagoya Institute of Technology (NITech)
3rd Author's Name Lantian Wei  
3rd Author's Affiliation Toyota Technological Institute (TTI)
4th Author's Name Tadashi Wadayama  
4th Author's Affiliation Nagoya Institute of Technology (NITech)
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Speaker Author-1 
Date Time 2026-05-21 14:50:00 
Presentation Time 25 minutes 
Registration for IT 
Paper # IT2026-5, EMM2026-5 
Volume (vol) vol.126 
Number (no) no.29(IT), no.30(EMM) 
Page pp.24-29 
#Pages 6 
Date of Issue 2026-05-14 (IT, EMM) 

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