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A globally convergent conjugate gradient method for minimizing self-concordant functions with application to constrained optimisation problems

dc.contributor.authorJi, H
dc.contributor.authorHuang, M
dc.contributor.authorMoore, JB
dc.contributor.authorManton, JH
dc.date.available2014-05-22T04:29:09Z
dc.date.issued2007-12-01
dc.identifier.citationJi, H., Huang, M., Moore, J. B. & Manton, J. H. (2007). A globally convergent conjugate gradient method for minimizing self-concordant functions with application to constrained optimisation problems. Proceedings of the American Control Conference, pp.540-545. IEEE. https://doi.org/10.1109/ACC.2007.4282797.
dc.identifier.isbn1424409888
dc.identifier.isbn9781424409884
dc.identifier.issn0743-1619
dc.identifier.urihttp://hdl.handle.net/11343/31881
dc.descriptionAmerican Control Conference
dc.publisherIEEE
dc.source2007 American Control Conference
dc.subjectArtificial Intelligence and Image Processing
dc.titleA globally convergent conjugate gradient method for minimizing self-concordant functions with application to constrained optimisation problems
dc.typeConference Paper
dc.identifier.doi10.1109/ACC.2007.4282797
melbourne.peerreviewPeer Reviewed
melbourne.affiliationThe University of Melbourne
melbourne.affiliation.departmentElectrical and Electronic Engineering
melbourne.source.titleProceedings of the American Control Conference
melbourne.source.pages540-545
melbourne.publicationid127399
melbourne.elementsid311450
melbourne.contributor.authorManton, Jonathan
melbourne.internal.ingestnoteAbstract bulk upload (2017-07-24)
melbourne.accessrightsThis item is currently not available from this repository


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