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Paper Abstract and Keywords
Presentation 2012-11-07 15:30
Online Large-margin Weight Learning for First-order Logic-based Abduction
Naoya Inoue, Kazeto Yamamoto, Yotaro Watanabe, Naoaki Okazaki, Kentaro Inui (Tohoku Univ.) IBISML2012-54
Abstract (in Japanese) (See Japanese page) 
(in English) Abduction is inference to the best explanation. Abduction has long been studied in a wide range of contexts and is widely used for modeling artificial intelligence systems, such as diagnostic systems and plan recognition systems. However, less attention has been paid to how to automatically learn score functions, which rank explanations in order of their plausibility. In this paper, we propose a supervised learning approach for first-order logic-based abduction. The contribution of this paper is the following: (i) we show how to formulate the machine learning problem of abduction with the framework of online large-margin training, which has been shown to have both predictive performance and scalability to larger problems; (ii) we extend the state-of-the-art abductive reasoning system to model the score function with a weighted linear model, which is the groundwork for the online large-margin training; (iii) we support partially-specified gold-standard explanations as training examples, where the weights are learned to rank any explanation that includes the gold-standard explanation as the best explanation; (iv) the all-in-one software package for inference and learning is made publicly available.
Keyword (in Japanese) (See Japanese page) 
(in English) Abduction / Logic-based Reasoning / Online learning / Large-margin training / Structured learning / Latent variables / Passive Aggressive algorithm /  
Reference Info. IEICE Tech. Rep., vol. 112, no. 279, IBISML2012-54, pp. 143-150, Nov. 2012.
Paper # IBISML2012-54 
Date of Issue 2012-10-31 (IBISML) 
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)
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Conference Information
Committee IBISML  
Conference Date 2012-11-07 - 2012-11-09 
Place (in Japanese) (See Japanese page) 
Place (in English) Bunkyo School Building, Tokyo Campus, Tsukuba Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) the 15th Information-Based Induction Sciences Workshop 
Paper Information
Registration To IBISML 
Conference Code 2012-11-IBISML 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Online Large-margin Weight Learning for First-order Logic-based Abduction 
Sub Title (in English)  
Keyword(1) Abduction  
Keyword(2) Logic-based Reasoning  
Keyword(3) Online learning  
Keyword(4) Large-margin training  
Keyword(5) Structured learning  
Keyword(6) Latent variables  
Keyword(7) Passive Aggressive algorithm  
1st Author's Name Naoya Inoue  
1st Author's Affiliation Tohoku University (Tohoku Univ.)
2nd Author's Name Kazeto Yamamoto  
2nd Author's Affiliation Tohoku University (Tohoku Univ.)
3rd Author's Name Yotaro Watanabe  
3rd Author's Affiliation Tohoku University (Tohoku Univ.)
4th Author's Name Naoaki Okazaki  
4th Author's Affiliation Tohoku University (Tohoku Univ.)
5th Author's Name Kentaro Inui  
5th Author's Affiliation Tohoku University (Tohoku Univ.)
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Speaker Author-1 
Date Time 2012-11-07 15:30:00 
Presentation Time 150 minutes 
Registration for IBISML 
Paper # IBISML2012-54 
Volume (vol) vol.112 
Number (no) no.279 
Page pp.143-150 
Date of Issue 2012-10-31 (IBISML) 

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