IEICE Technical Committee Submission System
Conference Paper's Information
Online Proceedings
[Sign in]
Tech. Rep. Archives
 Go Top Page Go Previous   [Japanese] / [English] 

Paper Abstract and Keywords
Presentation 2021-03-02 10:50
Kernel tensor decomposition based unsupervised feature extraction -- Applications to bioinformatics --
Y-h. Taguchi (Chuo Univ.) IBISML2020-36
Abstract (in Japanese) (See Japanese page) 
(in English) A lot of research has been done on the so-called textit{large p small n} problem, where the number of samples is small compared to the number of variables.
In the so-called field of genome science, however, this ratio is extreme, with the number of genes (= number of variables = $p$) being tens of thousands while the number of subjects (= number of samples = $n$) is even a few, and $p/n sim 10^3$ is not uncommon. In such extreme cases, many of the methods proposed for the so-called textit{large p small n}problem are often ineffective. We have proposed ``Principal component analysis and tensor decomposition based unsupervised feature extraction'' to deal with this problem.
In the past decade, we have applied this method to many researches in the field of bioinformatics. However, this method is purely within the scope of linear algebra, and since it is unsupervised learning, there is no tuning parameter, and if the method does not work, there is no choice but to give up on the analysis itself. In order to solve this problem, we have developed a kernel version of the method. In this paper, we report on how we succeeded in kernelizing the method to solve this problem, which enables the method to take nonlinear relationships into account and greatly expands its application range.
Keyword (in Japanese) (See Japanese page) 
(in English) Tensor decomposition / Kernel trick / Feature selection / Unsupervised learning / / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 395, IBISML2020-36, pp. 16-23, March 2021.
Paper # IBISML2020-36 
Date of Issue 2021-02-23 (IBISML) 
ISSN 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. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF IBISML2020-36

Conference Information
Committee IBISML  
Conference Date 2021-03-02 - 2021-03-04 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Organized and general sessions on machine learning 
Paper Information
Registration To IBISML 
Conference Code 2021-03-IBISML 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Kernel tensor decomposition based unsupervised feature extraction 
Sub Title (in English) Applications to bioinformatics 
Keyword(1) Tensor decomposition  
Keyword(2) Kernel trick  
Keyword(3) Feature selection  
Keyword(4) Unsupervised learning  
1st Author's Name Y-h. Taguchi  
1st Author's Affiliation Chuo University (Chuo Univ.)
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 ()
Speaker Author-1 
Date Time 2021-03-02 10:50:00 
Presentation Time 25 minutes 
Registration for IBISML 
Paper # IBISML2020-36 
Volume (vol) vol.120 
Number (no) no.395 
Page pp.16-23 
Date of Issue 2021-02-23 (IBISML) 

[Return to Top Page]

[Return to IEICE Web Page]

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