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Paper Abstract and Keywords
Presentation 2010-11-30 14:30
[Invited Talk] Recent Advances in Information-Theoretic Learning Theory -- Tracking Latent Dynamics --
Kenji Yamanishi (Univ. of Tokyo) IT2010-51
Abstract (in Japanese) (See Japanese page) 
(in English) This paper addresses the issue of detecting changes of latent strucures behind data.The theory of probabilsitic models with latent variales has extensively been explored in the area of statistics and machine learning, and most research on it have mainly focused on
the static nature of that model.In this paper we rather consider the case where the probabilisitic model with latent variables changes over time and our main concern is how to track the structural changes of the model. Various approaches have been taken to address this issue. They include modern techniques of information-theoretic learning theory such as "tracking best experts","switching distributions","dynamic model selection."They form a novel trend of information theory and learning theory and have been applied to data mining issues such as novelty detection, network structural change detection.
This paper overviews recent advances in the theory of detecting changes of latent structures and its applications to real problems.
Keyword (in Japanese) (See Japanese page) 
(in English) latent dynamics / MDL principle / dynamic model selection / switching theory / data mining / novelty detection / anomaly detection / Information-theoretic learning theory  
Reference Info. IEICE Tech. Rep., vol. 110, no. 320, IT2010-51, pp. 1-8, Nov. 2010.
Paper # IT2010-51 
Date of Issue 2010-11-23 (IT) 
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 IT  
Conference Date 2010-11-30 - 2010-11-30 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To IT 
Conference Code 2010-11-IT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Recent Advances in Information-Theoretic Learning Theory 
Sub Title (in English) Tracking Latent Dynamics 
Keyword(1) latent dynamics  
Keyword(2) MDL principle  
Keyword(3) dynamic model selection  
Keyword(4) switching theory  
Keyword(5) data mining  
Keyword(6) novelty detection  
Keyword(7) anomaly detection  
Keyword(8) Information-theoretic learning theory  
1st Author's Name Kenji Yamanishi  
1st Author's Affiliation The University of Tokyo (Univ. of Tokyo)
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Speaker Author-1 
Date Time 2010-11-30 14:30:00 
Presentation Time 50 minutes 
Registration for IT 
Paper # IT2010-51 
Volume (vol) vol.110 
Number (no) no.320 
Page pp.1-8 
#Pages 8 
Date of Issue 2010-11-23 (IT) 

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