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Variational Spectral Analysis

dc.contributor.authorSendov, Hristoen
dc.date.accessioned2006-08-22T14:24:18Z
dc.date.available2006-08-22T14:24:18Z
dc.date.issued2000en
dc.date.submitted2000en
dc.description.abstractWe present results on smooth and nonsmooth variational properties of {it symmetric} functions of the eigenvalues of a real symmetric matrix argument, as well as {it absolutely symmetric} functions of the singular values of a real rectangular matrix. Such results underpin the theory of optimization problems involving such functions. We answer the question of when a symmetric function of the eigenvalues allows a quadratic expansion around a matrix, and then the stronger question of when it is twice differentiable. We develop simple formulae for the most important nonsmooth subdifferentials of functions depending on the singular values of a real rectangular matrix argument and give several examples. The analysis of the above two classes of functions may be generalized in various larger abstract frameworks. In particular, we investigate how functions depending on the eigenvalues or the singular values of a matrix argument may be viewed as the composition of symmetric functions with the roots of {it hyperbolic polynomials}. We extend the relationship between hyperbolic polynomials and {it self-concordant barriers} (an extremely important class of functions in contemporary interior point methods for convex optimization) by exhibiting a new class of self-concordant barriers obtainable from hyperbolic polynomials.en
dc.formatapplication/pdfen
dc.format.extent1255011 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/10012/1089
dc.language.isoenen
dc.pendingfalseen
dc.publisherUniversity of Waterlooen
dc.rightsCopyright: 2000, Sendov, Hristo. All rights reserved.en
dc.subjectMathematicsen
dc.subjecteigenvaluesen
dc.subjecthyperbolic polynomialsen
dc.subjectsingular valuesen
dc.subjectself-concordant barriersen
dc.subjectvariational analysisen
dc.subjectspectral functionsen
dc.titleVariational Spectral Analysisen
dc.typeDoctoral Thesisen
uws-etd.degreeDoctor of Philosophyen
uws-etd.degree.departmentCombinatorics and Optimizationen
uws.peerReviewStatusUnrevieweden
uws.scholarLevelGraduateen
uws.typeOfResourceTexten

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