Paper Abstract and Keywords |
Presentation |
2013-11-12 15:45
[Poster Presentation]
Non-Convex Optimization of Robust Support Vector Regression by Utilizing Parametric Programming Shinya Suzumura, Ichiro Takeuchi (Nagoya Inst. of Tech.), Masashi Sugiyama (Tokyo Inst. of Tech.) IBISML2013-45 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In this paper, we propose a novel optimization method for robust support vector regression(SVR) that has robustness to outliers. In robust SVR, it is important to adaptively determine which instances are considered as outliers, and how much the effect of outliers should be alleviated. We introduce a pair of tuning parameters that adjust the outlier's criterion and effects, and develop a parametric algorithm that computes the path of solutions when those parameters are continuously changed.
Since the loss function of robust SVR is non-convex, our proposed algorithm computes a path of local optimal solutions. Unlike solution paths of convex problems, our local optimal solution path are shown to have finite number of discrete points. Our algorithm can identify those discrete points and properly handle those discontinuities in the path computation.
Although we have already proposed similar optimaization method for support vector classification, we propose the regression version of our method here. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Robust Support Vector Regression / Parametric Programming / Non-Convex Optimization / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 113, no. 286, IBISML2013-45, pp. 69-75, Nov. 2013. |
Paper # |
IBISML2013-45 |
Date of Issue |
2013-11-05 (IBISML) |
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) |
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IBISML2013-45 |
Conference Information |
Committee |
IBISML |
Conference Date |
2013-11-10 - 2013-11-13 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Tokyo Institute of Technology, Kuramae-Kaikan |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
The 16th IBIS Workshop & The 2nd IBIS Tutorial |
Paper Information |
Registration To |
IBISML |
Conference Code |
2013-11-IBISML |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Non-Convex Optimization of Robust Support Vector Regression by Utilizing Parametric Programming |
Sub Title (in English) |
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Keyword(1) |
Robust Support Vector Regression |
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Parametric Programming |
Keyword(3) |
Non-Convex Optimization |
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1st Author's Name |
Shinya Suzumura |
1st Author's Affiliation |
Nagoya Institute of Technology (Nagoya Inst. of Tech.) |
2nd Author's Name |
Ichiro Takeuchi |
2nd Author's Affiliation |
Nagoya Institute of Technology (Nagoya Inst. of Tech.) |
3rd Author's Name |
Masashi Sugiyama |
3rd Author's Affiliation |
Tokyo institute of technology (Tokyo Inst. of Tech.) |
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Speaker |
Author-1 |
Date Time |
2013-11-12 15:45:00 |
Presentation Time |
180 minutes |
Registration for |
IBISML |
Paper # |
IBISML2013-45 |
Volume (vol) |
vol.113 |
Number (no) |
no.286 |
Page |
pp.69-75 |
#Pages |
7 |
Date of Issue |
2013-11-05 (IBISML) |
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