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Paper Abstract and Keywords
Presentation 2021-10-08 10:00
[Tutorial Lecture] The Past and The Future of Explainable AI Techniques
Yoshitaka Kameya (Meijo Univ.) SIS2021-17
Abstract (in Japanese) (See Japanese page) 
(in English) Machine learning models of high predictive performance, such as deep neural networks and ensemble models, now play a central role in the current artificial intelligence technologies, and have started to be applied to the problems related to our health or properties. However, one of the primary obstacles here is the opacity of such high-performance models. So far, dozens of techniques for reducing the opacity have been explored, and form a research field called ``explainable aritificial intelligence (XAI).'' In this paper, I review the past literature on XAI, organize key concepts and techniques in the current XAI research, and discuss the future direction of XAI.
Keyword (in Japanese) (See Japanese page) 
(in English) explainable AI / XAI / machine learning / deep learning / / / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 190, SIS2021-17, pp. 36-41, Oct. 2021.
Paper # SIS2021-17 
Date of Issue 2021-09-30 (SIS) 
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 SIS2021-17

Conference Information
Committee SIS ITE-BCT  
Conference Date 2021-10-07 - 2021-10-08 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) System Implementation Technology, Short Range Wireless Systems, Smart Multimedia Systems, Broadcasting Technology, etc. 
Paper Information
Registration To SIS 
Conference Code 2021-10-SIS-BCT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) The Past and The Future of Explainable AI Techniques 
Sub Title (in English)  
Keyword(1) explainable AI  
Keyword(2) XAI  
Keyword(3) machine learning  
Keyword(4) deep learning  
1st Author's Name Yoshitaka Kameya  
1st Author's Affiliation Meijo University (Meijo Univ.)
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Date Time 2021-10-08 10:00:00 
Presentation Time 40 
Registration for SIS 
Paper # IEICE-SIS2021-17 
Volume (vol) IEICE-121 
Number (no) no.190 
Page pp.36-41 
#Pages IEICE-6 
Date of Issue IEICE-SIS-2021-09-30 

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