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Paper Abstract and Keywords
Presentation 2013-07-23 16:00
Gibbs Sampling Estimation of Maximum Margin Supervised Topic Models for Regression
Ryosuke Ueno, Koji Eguchi (Kobe Univ.) DE2013-31
Abstract (in Japanese) (See Japanese page) 
(in English) Regression based on latent topics is one of the promising approaches for analyzing a collection of documents associated with continuous labels. MedLDA is one such model that was proposed recently. For the inference of MedLDA, a variational Bayesian method has been used. Very recently, some other inference methods such as collapsed Gibbs sampling have been applied to this model; however, they have not been sufficiently explored. In this paper, we formulate an inference method based on collapsed Gibbs sampling for MedLDA for the purpose of regression analysis, and show the results of experimental evaluation.
Keyword (in Japanese) (See Japanese page) 
(in English) topic model / maximum margin / Gibbs sampling / regression analysis / / / /  
Reference Info. IEICE Tech. Rep., vol. 113, no. 150, DE2013-31, pp. 187-192, July 2013.
Paper # DE2013-31 
Date of Issue 2013-07-15 (DE) 
ISSN Print edition: ISSN 0913-5685    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)
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Conference Information
Committee DE IPSJ-DBS IPSJ-IFAT  
Conference Date 2013-07-22 - 2013-07-23 
Place (in Japanese) (See Japanese page) 
Place (in English) Hokkaido University 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Data Management, Information Search and Knowledge Retrieval for Big Data, etc. 
Paper Information
Registration To DE 
Conference Code 2013-07-DE-DBS-IFAT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Gibbs Sampling Estimation of Maximum Margin Supervised Topic Models for Regression 
Sub Title (in English)  
Keyword(1) topic model  
Keyword(2) maximum margin  
Keyword(3) Gibbs sampling  
Keyword(4) regression analysis  
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1st Author's Name Ryosuke Ueno  
1st Author's Affiliation Kobe University (Kobe Univ.)
2nd Author's Name Koji Eguchi  
2nd Author's Affiliation Kobe University (Kobe Univ.)
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Speaker Author-1 
Date Time 2013-07-23 16:00:00 
Presentation Time 40 minutes 
Registration for DE 
Paper # DE2013-31 
Volume (vol) vol.113 
Number (no) no.150 
Page pp.187-192 
#Pages
Date of Issue 2013-07-15 (DE) 


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