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Paper Abstract and Keywords
Presentation 2021-03-03 10:00
A Constrained Alternating Minimization Approach to End-to-End Graph Signal Denoising
Eisuke Yamagata, Shunsuke Ono (Titech) EA2020-59 SIP2020-90 SP2020-24
Abstract (in Japanese) (See Japanese page) 
(in English) This paper proposes a denoising method for smooth graph signals observed on a graph of unknown topology. The proposed method is motivated by GL-SigRep, which can be in interpreted as a denoising method considering that it outputs a denoised signal as well as the learned laplacian. Although GL-SigRep is an effective alternative optimization algorithm for graph learning, its denoising performance is not always optimal due to its regularization parameter, which appears in both denoising and graph learning phase of optimization, making parameter tuning difficult. In this paper, we modify GL-SigRep's formulation to simplify its parameter tuning and illustrate the advantageous experimental results over synthetic data.
Keyword (in Japanese) (See Japanese page) 
(in English) Graph signal processing / graph signal denoising / graph learning / alternating minimization / constrained optimization / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 398, SIP2020-90, pp. 1-4, March 2021.
Paper # SIP2020-90 
Date of Issue 2021-02-24 (EA, SIP, SP) 
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 EA2020-59 SIP2020-90 SP2020-24

Conference Information
Committee EA US SP SIP IPSJ-SLP  
Conference Date 2021-03-03 - 2021-03-04 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Speech, Engineering/Electro Acoustics, Signal Processing, Ultrasonics, and Related Topics 
Paper Information
Registration To SIP 
Conference Code 2021-03-EA-US-SP-SIP-SLP 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Constrained Alternating Minimization Approach to End-to-End Graph Signal Denoising 
Sub Title (in English)  
Keyword(1) Graph signal processing  
Keyword(2) graph signal denoising  
Keyword(3) graph learning  
Keyword(4) alternating minimization  
Keyword(5) constrained optimization  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Eisuke Yamagata  
1st Author's Affiliation Tokyo Institute of Technology (Titech)
2nd Author's Name Shunsuke Ono  
2nd Author's Affiliation Tokyo Institute of Technology (Titech)
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Speaker Author-1 
Date Time 2021-03-03 10:00:00 
Presentation Time 25 minutes 
Registration for SIP 
Paper # EA2020-59, SIP2020-90, SP2020-24 
Volume (vol) vol.120 
Number (no) no.397(EA), no.398(SIP), no.399(SP) 
Page pp.1-4 
#Pages 4 
Date of Issue 2021-02-24 (EA, SIP, SP) 

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