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Paper Abstract and Keywords
Presentation 2023-03-14 15:20
Estimation Performance of Sparse Bayesian Linear Regression model with t-distribution
Kazuaki Murayama (UEC) IT2022-105 ISEC2022-84 WBS2022-102 RCC2022-102
Abstract (in Japanese) (See Japanese page) 
(in English) In the sparse estimation with linear regression model, the t-distribution can be used as a prior distribution. We analyze an estimation performance of the method in the asymptotic case where the sample size and the number of regression coefficients both increase. This issue includes two aspects. One is the dependence of performance on the hyperparameters in prior distribution and the other is how the performance depends on the sample size and the number of nonzero components in regression coefficients. To perform analysis, we use methods of statistical mechanics in physics. An analog of thermodynamic potential is calculated based on some similarities between Bayes inference and statistical mechanics. A thermodynamic potential for a physical system is known to provide physical quantities. Alternatively, the analog of thermodynamic potential calculated in this paper provides the asymptotic evaluation of estimation performance.
Keyword (in Japanese) (See Japanese page) 
(in English) Linear Regression Model / Bayes Inference / Sparse Estimation / / / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 427, IT2022-105, pp. 236-241, March 2023.
Paper # IT2022-105 
Date of Issue 2023-03-07 (IT, ISEC, WBS, RCC) 
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 IT2022-105 ISEC2022-84 WBS2022-102 RCC2022-102

Conference Information
Committee RCC ISEC IT WBS  
Conference Date 2023-03-14 - 2023-03-15 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
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Paper Information
Registration To IT 
Conference Code 2023-03-RCC-ISEC-IT-WBS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Estimation Performance of Sparse Bayesian Linear Regression model with t-distribution 
Sub Title (in English)  
Keyword(1) Linear Regression Model  
Keyword(2) Bayes Inference  
Keyword(3) Sparse Estimation  
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1st Author's Name Kazuaki Murayama  
1st Author's Affiliation The University of Electro-Communications (UEC)
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Speaker Author-1 
Date Time 2023-03-14 15:20:00 
Presentation Time 25 minutes 
Registration for IT 
Paper # IT2022-105, ISEC2022-84, WBS2022-102, RCC2022-102 
Volume (vol) vol.122 
Number (no) no.427(IT), no.428(ISEC), no.429(WBS), no.430(RCC) 
Page pp.236-241 
#Pages 6 
Date of Issue 2023-03-07 (IT, ISEC, WBS, RCC) 

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