Presentation | 2009-11-11 Experimental Evaluation of a Two-Phase Sequential Partial Optimization Algorithm for Convex Quadratic Programming Problems Yuta KOBAYASHI, Norikazu TAKAHASHI, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | A convex quadratic programming (QP) problem is an optimization problem in which a convex quadratic function is minimized subject to some linear constraints. QP problems play important roles in many fields. Recently, the authors have proposed a two-phase sequential partial optimization algorithm for solving general convex QP problems, which is based on the decomposition method for the training of support vector machines. In this report, we describe the algorithm in detail and present experimental results to evaluate its performance. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | convex quadratic programming problem / sequential partial optimization / support vector machine / Scilab |
Paper # | NLP2009-97 |
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Committee | NLP |
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Conference Date | 2009/11/4(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Nonlinear Problems (NLP) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Experimental Evaluation of a Two-Phase Sequential Partial Optimization Algorithm for Convex Quadratic Programming Problems |
Sub Title (in English) | |
Keyword(1) | convex quadratic programming problem |
Keyword(2) | sequential partial optimization |
Keyword(3) | support vector machine |
Keyword(4) | Scilab |
1st Author's Name | Yuta KOBAYASHI |
1st Author's Affiliation | Graduate School of Information Science and Electrical Engineering, Kyushu University() |
2nd Author's Name | Norikazu TAKAHASHI |
2nd Author's Affiliation | Faculty of Information Science and Electrical Engineering, Kyushu University |
Date | 2009-11-11 |
Paper # | NLP2009-97 |
Volume (vol) | vol.109 |
Number (no) | 269 |
Page | pp.pp.- |
#Pages | 6 |
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