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Paper Abstract and Keywords
Presentation 2009-08-31 14:40
[Special Talk] Optimization algorithms for sparse regularization and multiple kernel learning and their applications to CV/PR
Ryota Tomioka, Taiji Suzuki, Masashi Sugiyama (Univ. of Tokyo.) PRMU2009-63
Abstract (in Japanese) (See Japanese page) 
(in English) Convex sparse regularization is increasingly becoming recognized as a principled
framework for selecting informative features and combining heterogeneous
data sources in machine learning. However training these models remains
a challenging task due to the non-differentiability of the resulting
optimization objective. In this paper, we derive a new algorithmic
framework for training various sparse regularized linear models under
general convex loss functions from the proximal minimization
framework. Connection to existing methods are also discussed.
Keyword (in Japanese) (See Japanese page) 
(in English) Regularization / Convex optimization / Multiple kernel learning / Augmented Lagrangian method / / / /  
Reference Info. IEICE Tech. Rep., vol. 109, no. 182, PRMU2009-63, pp. 43-48, Aug. 2009.
Paper # PRMU2009-63 
Date of Issue 2009-08-24 (PRMU) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
and
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)
Download PDF PRMU2009-63

Conference Information
Committee PRMU  
Conference Date 2009-08-31 - 2009-09-01 
Place (in Japanese) (See Japanese page) 
Place (in English) Tohoku Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To PRMU 
Conference Code 2009-08-PRMU 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Optimization algorithms for sparse regularization and multiple kernel learning and their applications to CV/PR 
Sub Title (in English)  
Keyword(1) Regularization  
Keyword(2) Convex optimization  
Keyword(3) Multiple kernel learning  
Keyword(4) Augmented Lagrangian method  
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1st Author's Name Ryota Tomioka  
1st Author's Affiliation The University of Tokyo (Univ. of Tokyo.)
2nd Author's Name Taiji Suzuki  
2nd Author's Affiliation The University of Tokyo (Univ. of Tokyo.)
3rd Author's Name Masashi Sugiyama  
3rd Author's Affiliation The University of Tokyo (Univ. of Tokyo.)
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Speaker Author-1 
Date Time 2009-08-31 14:40:00 
Presentation Time 90 minutes 
Registration for PRMU 
Paper # PRMU2009-63 
Volume (vol) vol.109 
Number (no) no.182 
Page pp.43-48 
#Pages 6 
Date of Issue 2009-08-24 (PRMU) 

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