Presentation 2014-01-23
Multi-Class Support Vector Machine based on Minimum Classification Error Criterion
Hisashi UEHARA, Hideyuki WATANABE, Shigeru KATAGIRI, Miho OHSAKI, Shigeki MATSUDA, Chiori HORI,
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Abstract(in English) Gradient-descent-based optimization methods used in Minimum Classification Error (MCE) training are not necessarily easily-handled, because they often require careful devices to minimize the non-convex objective of MCE training. To alleviate this difficulty, we propose in this paper a new training method by applying the optimization method of Multi-class Support Vector Machine, which runs fast and does not need know-how, to the MCE method. This application is realized by replacing the non-convex objective of MCE training with a new auxiliary function that is easy to optimize. The paper introduces the definition of proposed method in detail and it briefly reports experimental evaluation results for the proposed method.
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Keyword(in English) Minimum classification error training / Multi-class support vector machine / Auxiliary function method / Kernel
Paper # PRMU2013-93,MVE2013-34
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Conference Information
Committee MVE
Conference Date 2014/1/16(1days)
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Paper Information
Registration To Media Experience and Virtual Environment (MVE)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Multi-Class Support Vector Machine based on Minimum Classification Error Criterion
Sub Title (in English)
Keyword(1) Minimum classification error training
Keyword(2) Multi-class support vector machine
Keyword(3) Auxiliary function method
Keyword(4) Kernel
1st Author's Name Hisashi UEHARA
1st Author's Affiliation Doshisha University()
2nd Author's Name Hideyuki WATANABE
2nd Author's Affiliation NICT
3rd Author's Name Shigeru KATAGIRI
3rd Author's Affiliation Doshisha University
4th Author's Name Miho OHSAKI
4th Author's Affiliation Doshisha University
5th Author's Name Shigeki MATSUDA
5th Author's Affiliation NICT
6th Author's Name Chiori HORI
6th Author's Affiliation NICT
Date 2014-01-23
Paper # PRMU2013-93,MVE2013-34
Volume (vol) vol.113
Number (no) 403
Page pp.pp.-
#Pages 6
Date of Issue