IEICE Technical Committee Submission System
Conference Paper's Information
Online Proceedings
[Sign in]
... (for ESS/CS/ES/ISS)
Tech. Rep. Archives
... (for ES/CS)
 Go Top Page Go Previous   [Japanese] / [English] 

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
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  
1st Author's Name Keisuke Yamazaki  
1st Author's Affiliation Tokyo Institute of Technology (Tokyo Inst. of Tech.)
2nd Author's Name  
2nd Author's Affiliation ()
3rd Author's Name  
3rd Author's Affiliation ()
4th Author's Name  
4th Author's Affiliation ()
5th Author's Name  
5th Author's Affiliation ()
6th Author's Name  
6th Author's Affiliation ()
7th Author's Name  
7th Author's Affiliation ()
8th Author's Name  
8th Author's Affiliation ()
9th Author's Name  
9th Author's Affiliation ()
10th Author's Name  
10th Author's Affiliation ()
11th Author's Name  
11th Author's Affiliation ()
12th Author's Name  
12th Author's Affiliation ()
13th Author's Name  
13th Author's Affiliation ()
14th Author's Name  
14th Author's Affiliation ()
15th Author's Name  
15th Author's Affiliation ()
16th Author's Name  
16th Author's Affiliation ()
17th Author's Name  
17th Author's Affiliation ()
18th Author's Name  
18th Author's Affiliation ()
19th Author's Name  
19th Author's Affiliation ()
20th Author's Name  
20th Author's Affiliation ()
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 

[Return to Top Page]

[Return to IEICE Web Page]

The Institute of Electronics, Information and Communication Engineers (IEICE), Japan