QUADRATIC AND CONVEX MINIMAX CLASSIFICATION PROBLEMS
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- Kitahara Tomonari
- Tokyo Institute of Technology
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- Mizuno Shinji
- Tokyo Institute of Technology
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- Nakata Kazuhide
- Tokyo Institute of Technology
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Abstract
When there are two classes whose mean vectors and covariance matrices are known, Lanckriet et al. [7] consider the Linear Minimax Classification (LMC) problem and they propose a method for solving it. In this paper we first discuss the Quadratic Minimax Classification (QMC) problem, which is a generalization of LMC. We show that QMC is transformed to a parametric Semidefinite Programming (SDP) problem. We further define the Convex Minimax Classification (CMC) problem. Though the two problems are generalizations of LMC, we prove that solutions of these problems can be obtained by solving LMC.
Journal
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- Journal of the Operations Research Society of Japan
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Journal of the Operations Research Society of Japan 51 (2), 191-201, 2008
The Operations Research Society of Japan
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Details 詳細情報について
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- CRID
- 1390282679085901056
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- NII Article ID
- 110006792052
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- NII Book ID
- AA00703935
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- ISSN
- 21888299
- 04534514
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- NDL BIB ID
- 9544559
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- Text Lang
- en
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
- KAKEN
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- Abstract License Flag
- Disallowed