Global convergence analysis of decomposition methods for support vector machines

Norikazu Takahashi; Tetsuo Nishi

Global convergence analysis of decomposition methods for support vector machines

Research output: Contribution to journal › Conference article › peer-review

Abstract

Convergence property of decomposition methods for solving quadratic optimization problems arising in support vector machines is studied. It is shown that under a mild condition any decomposition method converges to an optimal solution.

Original language	English
Pages (from-to)	V-728-V-731
Journal	Proceedings - IEEE International Symposium on Circuits and Systems
Volume	5
Publication status	Published - Sept 6 2004
Externally published	Yes
Event	2004 IEEE International Symposium on Cirquits and Systems - Proceedings - Vancouver, BC, Canada Duration: May 23 2004 → May 26 2004

ASJC Scopus subject areas

Electrical and Electronic Engineering

Cite this

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title = "Global convergence analysis of decomposition methods for support vector machines",

abstract = "Convergence property of decomposition methods for solving quadratic optimization problems arising in support vector machines is studied. It is shown that under a mild condition any decomposition method converges to an optimal solution.",

author = "Norikazu Takahashi and Tetsuo Nishi",

year = "2004",

month = sep,

day = "6",

language = "English",

volume = "5",

pages = "V--728--V--731",

journal = "Proceedings - IEEE International Symposium on Circuits and Systems",

issn = "0271-4310",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "2004 IEEE International Symposium on Cirquits and Systems - Proceedings ; Conference date: 23-05-2004 Through 26-05-2004",

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TY - JOUR

T1 - Global convergence analysis of decomposition methods for support vector machines

AU - Takahashi, Norikazu

AU - Nishi, Tetsuo

PY - 2004/9/6

Y1 - 2004/9/6

N2 - Convergence property of decomposition methods for solving quadratic optimization problems arising in support vector machines is studied. It is shown that under a mild condition any decomposition method converges to an optimal solution.

AB - Convergence property of decomposition methods for solving quadratic optimization problems arising in support vector machines is studied. It is shown that under a mild condition any decomposition method converges to an optimal solution.

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M3 - Conference article

AN - SCOPUS:4344593856

SN - 0271-4310

VL - 5

SP - V-728-V-731

JO - Proceedings - IEEE International Symposium on Circuits and Systems

JF - Proceedings - IEEE International Symposium on Circuits and Systems

T2 - 2004 IEEE International Symposium on Cirquits and Systems - Proceedings

Y2 - 23 May 2004 through 26 May 2004

ER -

Global convergence analysis of decomposition methods for support vector machines

Abstract

ASJC Scopus subject areas

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