Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/2461
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DC Field | Value | Language |
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dc.contributor.author | To, K. | - |
dc.contributor.author | Lim, C. | - |
dc.contributor.author | Teo, K. | - |
dc.contributor.author | Liebelt, M. | - |
dc.date.issued | 2001 | - |
dc.identifier.citation | Nonlinear Analysis Theory Methods and Applications, 2001; 47(8 Part 8 Special Issue SI):5623-5633 | - |
dc.identifier.issn | 0362-546X | - |
dc.identifier.uri | http://hdl.handle.net/2440/2461 | - |
dc.description.abstract | We consider a support vector machine training problem involving a quadratic objective function with a single linear equality constraint and a box constraint. Using quadratic surjective space transformation to create a barrier for the gradient method, an iterative support vector learning algorithm is derived. We further derive a stable steepest descent method to find the stop-size in order to reduce the number of iterations to reach the optimal solution. This method offers speed improvement over the fixed step-size gradient method, in particular for QP problems with ill-conditioned Hessian. | - |
dc.description.statementofresponsibility | K. N. To, C. C. Lim, K. L. Teo and M. J. Liebelt | - |
dc.description.uri | http://www.elsevier.com/wps/find/journaldescription.cws_home/239/description#description | - |
dc.language.iso | en | - |
dc.publisher | Pergamon-Elsevier Science Ltd | - |
dc.source.uri | http://dx.doi.org/10.1016/s0362-546x(01)00664-2 | - |
dc.subject | Support vector machines | - |
dc.subject | quadratic programming | - |
dc.subject | barrier projection method | - |
dc.title | Support vector learning with quadratic programming and adaptive step size barrier-projection | - |
dc.type | Journal article | - |
dc.identifier.doi | 10.1016/S0362-546X(01)00664-2 | - |
pubs.publication-status | Published | - |
dc.identifier.orcid | Lim, C. [0000-0002-2463-9760] | - |
dc.identifier.orcid | Liebelt, M. [0000-0001-6610-2876] | - |
Appears in Collections: | Aurora harvest 2 Electrical and Electronic Engineering publications Environment Institute publications |
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