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Paper Abstract and Keywords
Presentation 2010-01-18 16:30
Necessary Data Length for HMMs Based on the Vicarious Bayes Learning
Keisuke Yamazaki (Tokyo Inst. of Tech.) NC2009-77
Abstract (in Japanese) (See Japanese page) 
(in English) The present paper analyzes the change of parameter learning due to feature selections and investigates
conditions to have the same learning result in both original and feature spaces. Moreover, we propose a fast and
precise learning method referred to as the vicarious Bayes learning. We also apply it to hidden Markov model and
derive a necessary length for the complete parameter learning.
Keyword (in Japanese) (See Japanese page) 
(in English) Feature Selection / Dimension Reduction / Bayes Learning / Algebraic Geometry / / / /  
Reference Info. IEICE Tech. Rep., vol. 109, no. 363, NC2009-77, pp. 37-42, Jan. 2010.
Paper # NC2009-77 
Date of Issue 2010-01-11 (NC) 
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. (No. 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF NC2009-77

Conference Information
Committee NC  
Conference Date 2010-01-18 - 2010-01-19 
Place (in Japanese) (See Japanese page) 
Place (in English) Hyakunen-Kinen in Hokkaido University 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Biomimetic information systems, Machine Learning 
Paper Information
Registration To NC 
Conference Code 2010-01-NC 
Language English (Japanese title is available) 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Necessary Data Length for HMMs Based on the Vicarious Bayes Learning 
Sub Title (in English)  
Keyword(1) Feature Selection  
Keyword(2) Dimension Reduction  
Keyword(3) Bayes Learning  
Keyword(4) Algebraic Geometry  
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1st Author's Name Keisuke Yamazaki  
1st Author's Affiliation Tokyo Institute of Technology (Tokyo Inst. of Tech.)
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Speaker
Date Time 2010-01-18 16:30:00 
Presentation Time 25 
Registration for NC 
Paper # IEICE-NC2009-77 
Volume (vol) IEICE-109 
Number (no) no.363 
Page pp.37-42 
#Pages IEICE-6 
Date of Issue IEICE-NC-2010-01-11 


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