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Paper Abstract and Keywords
Presentation 2018-11-05 15:10
[Poster Presentation] Compensated Integrated Gradients for Visualization of Features Contributing to EEG Classification
Kazuki Tachikawa, Yuji Kawai, Jihoon Park, Minoru Asada (Osaka Univ.) IBISML2018-76
Abstract (in Japanese) (See Japanese page) 
(in English) Integrated gradients method has been widely employed to evaluate the degrees of contribution of input features to classification because it satisfies the desirable axioms for the fair attributions of the contribution.
This method, however, requires an appropriate reference point (hyperparameter) for reliable attributions of the contribution.
We propose compensated integrated gradients method that do not require setting the reference point.
The method compensates the attributions calculated by integrated gradients at an arbitrary reference point using the Shapley sampling value.
We prove that the method can obtain reliable attributions if processes of input features are mutually independent and identical in a classifier.
Using three EEG datasets, we empirically demonstrated that the attributions of the proposed method was more reliable than those of the conventional integrated gradients method, and the computational complexity of the proposed model was much less than that of the Shapley sampling value.
Keyword (in Japanese) (See Japanese page) 
(in English) The Shapley value / Interpretability / EEG / Convolutional Neural Network / / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 284, IBISML2018-76, pp. 241-247, Nov. 2018.
Paper # IBISML2018-76 
Date of Issue 2018-10-29 (IBISML) 
ISSN Online edition: ISSN 2432-6380
Copyright
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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 IBISML  
Conference Date 2018-11-05 - 2018-11-07 
Place (in Japanese) (See Japanese page) 
Place (in English) Hokkaido Citizens Activites Center (Kaderu 2.7) 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Information-Based Induction Science Workshop (IBIS2018) 
Paper Information
Registration To IBISML 
Conference Code 2018-11-IBISML 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Compensated Integrated Gradients for Visualization of Features Contributing to EEG Classification 
Sub Title (in English)  
Keyword(1) The Shapley value  
Keyword(2) Interpretability  
Keyword(3) EEG  
Keyword(4) Convolutional Neural Network  
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1st Author's Name Kazuki Tachikawa  
1st Author's Affiliation Osaka Univercity (Osaka Univ.)
2nd Author's Name Yuji Kawai  
2nd Author's Affiliation Osaka Univercity (Osaka Univ.)
3rd Author's Name Jihoon Park  
3rd Author's Affiliation Osaka Univercity (Osaka Univ.)
4th Author's Name Minoru Asada  
4th Author's Affiliation Osaka Univercity (Osaka Univ.)
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Speaker Author-1 
Date Time 2018-11-05 15:10:00 
Presentation Time 180 minutes 
Registration for IBISML 
Paper # IBISML2018-76 
Volume (vol) vol.118 
Number (no) no.284 
Page pp.241-247 
#Pages
Date of Issue 2018-10-29 (IBISML) 


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