Comments on Quasi-Linear Support Vector Machine for Nonlinear Classification
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- KAMATA Sei-ichiro
- Graduate School of Information, Production and Systems, Waseda University
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- MINE Tsunenori
- Faculty of Information Science and Electrical Engineering, Kyushu University
Description
<p>In 2014, the above paper entitled ‘Quasi-Linear Support Vector Machine for Nonlinear Classification’ was published by Zhou, et al. [1]. They proposed a quasi-linear kernel function for support vector machine (SVM). However, in this letter, we point out that this proposed kernel function is a part of multiple kernel functions generated by well-known multiple kernel learning which is proposed by Bach, et al. [2] in 2004. Since then, there have been a lot of related papers on multiple kernel learning with several applications [3]. This letter verifies that the main kernel function proposed by Zhou, et al. [1] can be derived using multiple kernel learning algorithms [3]. In the kernel construction, Zhou, et al. [1] used Gaussian kernels, but the multiple kernel learning had already discussed the locality of additive Gaussian kernels or other kernels in the framework [4], [5]. Especially additive Gaussian or other kernels were discussed in tutorial at major international conference ECCV2012 [6]. The authors did not discuss these matters.</p>
Journal
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- IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
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IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E106.A (11), 1444-1445, 2023-11-01
The Institute of Electronics, Information and Communication Engineers
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Details 詳細情報について
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- CRID
- 1390297979838119552
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- ISSN
- 17451337
- 09168508
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- Text Lang
- en
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- Data Source
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- JaLC
- Crossref
- OpenAIRE
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- Abstract License Flag
- Disallowed