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Paper Abstract and Keywords
Presentation 2017-06-20 11:00
On Contributions of Principal Eigenfunctions of Covariance Operator of Kernel Feature Vectors to Relevant Information in Nonlinear Regression
Masahiro Yukawa (Keio Univ.), Klaus-Robert Muller (TU BerlinTechnical U) CAS2017-16 VLD2017-19 SIP2017-40 MSS2017-16
Abstract (in Japanese) (See Japanese page) 
(in English) We study, through simple non-asymptotic arguments, the contributions of eigenfunctions of the covariance operator of kernel feature vectors to the relevant information in nonlinear regression under the explicit centering. Although the contribution of an eigenfunction contains a term which decays as the same rate as the eigenvalues (as shown by Braun, Buhmann, and Muller in 2008), it also contains a constant term which comes from the centering operation. Our simple derivations lead to an exact analytic form of the contribution containing no truncation errors.
Keyword (in Japanese) (See Japanese page) 
(in English) nonlinear regression / kernel PCA / reproducing kernel Hilbert space / / / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 98, SIP2017-40, pp. 81-85, June 2017.
Paper # SIP2017-40 
Date of Issue 2017-06-12 (CAS, VLD, SIP, MSS) 
ISSN Print edition: ISSN 0913-5685    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 CAS2017-16 VLD2017-19 SIP2017-40 MSS2017-16

Conference Information
Committee SIP CAS MSS VLD  
Conference Date 2017-06-19 - 2017-06-20 
Place (in Japanese) (See Japanese page) 
Place (in English) Niigata University, Ikarashi Campus 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To SIP 
Conference Code 2017-06-SIP-CAS-MSS-VLD 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) On Contributions of Principal Eigenfunctions of Covariance Operator of Kernel Feature Vectors to Relevant Information in Nonlinear Regression 
Sub Title (in English)  
Keyword(1) nonlinear regression  
Keyword(2) kernel PCA  
Keyword(3) reproducing kernel Hilbert space  
1st Author's Name Masahiro Yukawa  
1st Author's Affiliation Keio University (Keio Univ.)
2nd Author's Name Klaus-Robert Muller  
2nd Author's Affiliation Technical University of Berlin (TU BerlinTechnical U)
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Speaker Author-1 
Date Time 2017-06-20 11:00:00 
Presentation Time 20 minutes 
Registration for SIP 
Paper # CAS2017-16, VLD2017-19, SIP2017-40, MSS2017-16 
Volume (vol) vol.117 
Number (no) no.96(CAS), no.97(VLD), no.98(SIP), no.99(MSS) 
Page pp.81-85 
Date of Issue 2017-06-12 (CAS, VLD, SIP, MSS) 

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