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Paper Abstract and Keywords
Presentation 2010-09-05 17:30
A Study on Feature Selection Path for High-Dimensional Local Classifiers
Ichiro Takeuchi (NIT) PRMU2010-71 IBISML2010-43
Abstract (in Japanese) (See Japanese page) 
(in English) We study feature selection and weighting problems for local-based classifier. The proposed algorithm is formulated as a regularized empirical loss minimization problem w.r.t. feature weights. We show that the solution of the problem yields sparse feature weights, and it enables us to select a subset of features by choosing an appropriate regularization parameter. Furthermore, we develop an algorithm to compute the entire regularization path of the problem. Feature weighting problem is defined using, what is called, {\it target-neighbors}, and they must be updated according to the change of feature weights. The proposed algorithm can detect target-neighbor changes by exploiting the piecewise-linearity of the regularization path. This leads us to construct a regularization path algorithm with target-neighbor updates. We show the effectiveness of the proposed algorithm through numerical experiments.
Keyword (in Japanese) (See Japanese page) 
(in English) local-based classifier / nearest-neighbor classifier / feature selection / feature weighting / convex optimization / path-following / parametric programming / metric learning  
Reference Info. IEICE Tech. Rep., vol. 110, no. 188, IBISML2010-43, pp. 105-112, Sept. 2010.
Paper # IBISML2010-43 
Date of Issue 2010-08-29 (PRMU, 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
Conference Date 2010-09-05 - 2010-09-06 
Place (in Japanese) (See Japanese page) 
Place (in English) Fukuoka Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Machine learning and optimization for computer vision and pattern recognition, etc. 
Paper Information
Registration To IBISML 
Conference Code 2010-09-IBISML-PRMU-CVIM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Study on Feature Selection Path for High-Dimensional Local Classifiers 
Sub Title (in English)  
Keyword(1) local-based classifier  
Keyword(2) nearest-neighbor classifier  
Keyword(3) feature selection  
Keyword(4) feature weighting  
Keyword(5) convex optimization  
Keyword(6) path-following  
Keyword(7) parametric programming  
Keyword(8) metric learning  
1st Author's Name Ichiro Takeuchi  
1st Author's Affiliation Nagoya Institute of Technology (NIT)
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Speaker Author-1 
Date Time 2010-09-05 17:30:00 
Presentation Time 30 minutes 
Registration for IBISML 
Paper # PRMU2010-71, IBISML2010-43 
Volume (vol) vol.110 
Number (no) no.187(PRMU), no.188(IBISML) 
Page pp.105-112 
Date of Issue 2010-08-29 (PRMU, IBISML) 

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