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Paper Abstract and Keywords
Presentation 2014-11-18 15:00
[Poster Presentation] Denoising High-dimensional Sequences with the Bidirectional Recurrent Restricted Boltzmann Machine
Shoken Kaneko (Yamaha Co.) IBISML2014-62
Abstract (in Japanese) (See Japanese page) 
(in English) We propose a probabilistic neural network for modeling high-dimensional sequences with complex non-linearities.
Our model is an extension of the previously introduced Recurrent Neural Network-Restricted Boltzmann Machine.
We extend the model by adding a backward recurrent chain, which makes bidirectional propagation of information possible
and allowing our model to incorporate knowledge of future observations.
Our model can be readily applied for tasks such as denoising of high-dimensional sequences.
We show that our model outperforms the unidirectional model in the task of denoising moving pictures of balls bouncing in a box,
reconstructing much smoother sequences.
Keyword (in Japanese) (See Japanese page) 
(in English) Machine Learning / Neural Networks / Recurrent Neural Network - Restricted Boltzmann Machines / / / / /  
Reference Info. IEICE Tech. Rep., vol. 114, no. 306, IBISML2014-62, pp. 207-212, Nov. 2014.
Paper # IBISML2014-62 
Date of Issue 2014-11-10 (IBISML) 
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)
Download PDF IBISML2014-62

Conference Information
Committee IBISML  
Conference Date 2014-11-17 - 2014-11-19 
Place (in Japanese) (See Japanese page) 
Place (in English) Nagoya Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To IBISML 
Conference Code 2014-11-IBISML 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Denoising High-dimensional Sequences with the Bidirectional Recurrent Restricted Boltzmann Machine 
Sub Title (in English)  
Keyword(1) Machine Learning  
Keyword(2) Neural Networks  
Keyword(3) Recurrent Neural Network - Restricted Boltzmann Machines  
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1st Author's Name Shoken Kaneko  
1st Author's Affiliation Yamaha Corporation (Yamaha Co.)
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Speaker Author-1 
Date Time 2014-11-18 15:00:00 
Presentation Time 180 minutes 
Registration for IBISML 
Paper # IBISML2014-62 
Volume (vol) vol.114 
Number (no) no.306 
Page pp.207-212 
#Pages 6 
Date of Issue 2014-11-10 (IBISML) 

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