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Paper Abstract and Keywords
Presentation 2014-09-02 16:15
Rates of convergence of the universal Bayesian measure for continuous data
Takanori Ayano, Joe Suzuki (Osaka Univ.) PRMU2014-53 IBISML2014-34
Abstract (in Japanese) (See Japanese page) 
(in English) It is very important to estimate the probability of the data series accurately for applying MDL information criterion.
For discrete data, it is known that the methods based on universal coding in information theory have high precision (universal Bayesian measures) and
are used in MDL.
Recently, Ryabko extended the universal Bayesian measures for discrete data to continuous data and
one gets to be able to apply MDL for not only discrete data but also continuous data.
In this presentation, we give the rates of convergence for the generalization error of the universal Bayesian measures for continuous data and
show that they achieve the optimal rate under a certain condition.
Keyword (in Japanese) (See Japanese page) 
(in English) MDL information criterion / universal code / density estimation / information theory / data compression / / /  
Reference Info. IEICE Tech. Rep., vol. 114, no. 198, IBISML2014-34, pp. 143-146, Sept. 2014.
Paper # IBISML2014-34 
Date of Issue 2014-08-25 (PRMU, IBISML) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
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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 PRMU IBISML IPSJ-CVIM  
Conference Date 2014-09-01 - 2014-09-02 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To IBISML 
Conference Code 2014-09-PRMU-IBISML-CVIM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Rates of convergence of the universal Bayesian measure for continuous data 
Sub Title (in English)  
Keyword(1) MDL information criterion  
Keyword(2) universal code  
Keyword(3) density estimation  
Keyword(4) information theory  
Keyword(5) data compression  
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1st Author's Name Takanori Ayano  
1st Author's Affiliation Osaka University (Osaka Univ.)
2nd Author's Name Joe Suzuki  
2nd Author's Affiliation Osaka University (Osaka Univ.)
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Date Time 2014-09-02 16:15:00 
Presentation Time 30 minutes 
Registration for IBISML 
Paper # PRMU2014-53, IBISML2014-34 
Volume (vol) vol.114 
Number (no) no.197(PRMU), no.198(IBISML) 
Page pp.143-146 
#Pages
Date of Issue 2014-08-25 (PRMU, IBISML) 


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