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Paper Abstract and Keywords
Presentation 2024-02-29 10:30
Accelerating and stabilizing vectorwise coordinate descent for spatially regularized independent low-rank matrix analysis
Yuto Ishikawa, Takuya Okubo, Norihiro Takamune (UTokyo), Tomohiko Nakamura (AIST), Daichi Kitamura (NIT Kagawa), Hiroshi Saruwatari (UTokyo), Yu Takahashi, Kazunobu Kondo (Yamaha) EA2023-68 SIP2023-115 SP2023-50
Abstract (in Japanese) (See Japanese page) 
(in English) Spatially regularized independent low-rank matrix analysis (SR-ILRMA) is the method that introduces the spatial prior information to independent low-rank matrix analysis, which is the state-of-the-art technique for blind source separation under overdetermined condition.SR-ILRMA uses an iterative update algorithm, vectorwise coordinate descent (VCD), to update a demixing filter.However, when implemented on a computer, VCD has the disadvantage of computational expensiveness because it involves many matrix operations in each iteration, such as two different inverse matrix operations.Therefore, in this paper, we propose a fast and stable algorithm by analytically equivalent transformations to the VCD update algorithm.Finally, numerical experiments verify the effectiveness of the proposed algorithm in terms of execution time and numerical stability.
Keyword (in Japanese) (See Japanese page) 
(in English) multichannel blind source separation / spatially regularized independent low-rank matrix analysis / vectorwise coordinate descent / / / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 401, EA2023-68, pp. 43-50, Feb. 2024.
Paper # EA2023-68 
Date of Issue 2024-02-22 (EA, SIP, SP) 
ISSN Online edition: ISSN 2432-6380
Copyright
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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 EA2023-68 SIP2023-115 SP2023-50

Conference Information
Committee SIP SP EA IPSJ-SLP  
Conference Date 2024-02-29 - 2024-03-01 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To EA 
Conference Code 2024-02-SIP-SP-EA-SLP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Accelerating and stabilizing vectorwise coordinate descent for spatially regularized independent low-rank matrix analysis 
Sub Title (in English)  
Keyword(1) multichannel blind source separation  
Keyword(2) spatially regularized independent low-rank matrix analysis  
Keyword(3) vectorwise coordinate descent  
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1st Author's Name Yuto Ishikawa  
1st Author's Affiliation The University of Tokyo (UTokyo)
2nd Author's Name Takuya Okubo  
2nd Author's Affiliation The University of Tokyo (UTokyo)
3rd Author's Name Norihiro Takamune  
3rd Author's Affiliation The University of Tokyo (UTokyo)
4th Author's Name Tomohiko Nakamura  
4th Author's Affiliation The National Institute of Advanced Industrial Science and Technology (AIST)
5th Author's Name Daichi Kitamura  
5th Author's Affiliation National Institute of Technology, Kagawa College (NIT Kagawa)
6th Author's Name Hiroshi Saruwatari  
6th Author's Affiliation The University of Tokyo (UTokyo)
7th Author's Name Yu Takahashi  
7th Author's Affiliation Yamaha Corporation (Yamaha)
8th Author's Name Kazunobu Kondo  
8th Author's Affiliation Yamaha Corporation (Yamaha)
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Speaker Author-1 
Date Time 2024-02-29 10:30:00 
Presentation Time 20 minutes 
Registration for EA 
Paper # EA2023-68, SIP2023-115, SP2023-50 
Volume (vol) vol.123 
Number (no) no.401(EA), no.402(SIP), no.403(SP) 
Page pp.43-50 
#Pages 8 
Date of Issue 2024-02-22 (EA, SIP, SP) 

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