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Paper Abstract and Keywords
Presentation 2018-09-21 09:40
Deep Learning and Related Technology -- Subspace Method and Hebbian Learning Revisited --
Ken-ichi Maeda PRMU2018-49 IBISML2018-26
Abstract (in Japanese) (See Japanese page) 
(in English) Deep Learning is recognised as the state-of-the-art AI technology, but it has several known problems. We discuss several related technologies for solving the peoblems. Subspace Method and Hebbian Learning are the topic technologies.
Keyword (in Japanese) (See Japanese page) 
(in English) Deep Learning / Subspace Method / Hebbian Learning / Multi-Layer Network / Linsker Network / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 220, IBISML2018-26, pp. 89-96, Sept. 2018.
Paper # IBISML2018-26 
Date of Issue 2018-09-13 (PRMU, IBISML) 
ISSN 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 PRMU2018-49 IBISML2018-26

Conference Information
Committee PRMU IBISML IPSJ-CVIM  
Conference Date 2018-09-20 - 2018-09-21 
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 2018-09-PRMU-IBISML-CVIM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Deep Learning and Related Technology 
Sub Title (in English) Subspace Method and Hebbian Learning Revisited 
Keyword(1) Deep Learning  
Keyword(2) Subspace Method  
Keyword(3) Hebbian Learning  
Keyword(4) Multi-Layer Network  
Keyword(5) Linsker Network  
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1st Author's Name Ken-ichi Maeda  
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Speaker Author-1 
Date Time 2018-09-21 09:40:00 
Presentation Time 10 minutes 
Registration for IBISML 
Paper # PRMU2018-49, IBISML2018-26 
Volume (vol) vol.118 
Number (no) no.219(PRMU), no.220(IBISML) 
Page pp.89-96 
#Pages 8 
Date of Issue 2018-09-13 (PRMU, IBISML) 

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