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Paper Abstract and Keywords
Presentation 2023-10-07 13:20
Proposal and evaluation of a distributed lasso algorithm based on alternating direction multiplier method
Naoki Toda, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) CAS2023-55 NLP2023-54
Abstract (in Japanese) (See Japanese page) 
(in English) Lasso is widely known as a sparse estimation method for regression coefficients in linear regression models, and the Alternating Direction Method of Multipliers (ADMM) is one of the representative computational methods for lasso. In this report, we propose an algorithm for multiple computers to execute the ADMM algorithm in a distributed manner under the situation where 1) the matrix of observed values of explanatory variables is partitioned in both row and column directions, 2) each block of the matrix is assigned to one computer, and 3) each computer can directly communicate with the four computers to which four blocks of the matrix adjacent to the block assigned to itself. The proposed algorithm performs an average consensus algorithm to compute the summation in ADMM, and solves the system of linear equations in a distributed manner by combining the Jacobi method with the average consensus algorithm. We conduct numerical experiments using synthetic and real-world data, demonstrating that the proposed algorithm can accurately estimate regression coefficients if the numbers of iterations for the average consensus algorithm, the Jacobi method and the lasso are appropriately set.
Keyword (in Japanese) (See Japanese page) 
(in English) consensus / distributed computation / lasso / alternating direction multiplier method / / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 203, NLP2023-54, pp. 111-116, Oct. 2023.
Paper # NLP2023-54 
Date of Issue 2023-09-29 (CAS, NLP) 
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 CAS2023-55 NLP2023-54

Conference Information
Committee NLP CAS  
Conference Date 2023-10-06 - 2023-10-07 
Place (in Japanese) (See Japanese page) 
Place (in English) Work plaza Gifu 
Topics (in Japanese) (See Japanese page) 
Topics (in English) CAS, NLP, etc. 
Paper Information
Registration To NLP 
Conference Code 2023-10-NLP-CAS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Proposal and evaluation of a distributed lasso algorithm based on alternating direction multiplier method 
Sub Title (in English)  
Keyword(1) consensus  
Keyword(2) distributed computation  
Keyword(3) lasso  
Keyword(4) alternating direction multiplier method  
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1st Author's Name Naoki Toda  
1st Author's Affiliation Okayama University (Okayama Univ.)
2nd Author's Name Tsuyoshi Migita  
2nd Author's Affiliation Okayama University (Okayama Univ.)
3rd Author's Name Norikazu Takahashi  
3rd Author's Affiliation Okayama University (Okayama Univ.)
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Speaker Author-1 
Date Time 2023-10-07 13:20:00 
Presentation Time 20 minutes 
Registration for NLP 
Paper # CAS2023-55, NLP2023-54 
Volume (vol) vol.123 
Number (no) no.202(CAS), no.203(NLP) 
Page pp.111-116 
#Pages 6 
Date of Issue 2023-09-29 (CAS, NLP) 

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