JMLR: Working Set Selection Using Second Order Information for ...

[[Redistributed from JMLR announce]]

~From: elm@xxxxxxxxxxxx
~Date: Thu, 15 Dec 2005 21:11:06 -0500
~Subject: [Jmlr-announce] Working Set Selection Using Second Order Information for Training Support Vector Machines

The Journal of Machine Learning Research (www.jmlr.org) is pleased to
announce publication of a new paper:
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Working Set Selection Using Second Order Information for Training
Support Vector Machines
Rong-En Fan, Pai-Hsuen Chen, Chih-Jen Lin
JMLR 6(Dec):1889--1918, 2005.

Abstract

Working set selection is an important step in decomposition methods for
training support vector machines (SVMs). This paper develops a new
technique for working set selection in SMO-type decomposition methods.
It uses second order information to achieve fast convergence.
Theoretical properties such as linear convergence are established.
Experiments demonstrate that the proposed method is faster than
existing selection methods using first order information.
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This paper and previous papers are available electronically at
http://www.jmlr.org in PDF format. The papers of Volumes 1-4 were also
published in hardcopy by MIT Press; please see
http://mitpress.mit.edu/JMLR for details. Volume 5 and subsequent
volumes will be printed in hardcopy by Microtome Publishing. Please see
http://www.mtome.com/Publications/jmlr.html for details and ordering
information.

-Erik G. Learned-Miller
elm@xxxxxxxxxxxx

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