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  • 1
    Online Resource
    Online Resource
    Boston, MA : Springer
    UID:
    gbv_1655350560
    Format: Online-Ressource (XVIII, 236 p, online resource)
    ISBN: 9781441988539
    Series Statement: Applied Optimization 87
    Content: This is the first elementary exposition of the main ideas of complexity theory for convex optimization. Up to now, most of the material can be found only in special journals and research monographs. The book covers optimal methods and lower complexity bounds for smooth and non-smooth convex optimization. A separate chapter is devoted to polynomial-time interior-point methods. Audience: The book is suitable for industrial engineers and economists
    Additional Edition: ISBN 9781461346913
    Additional Edition: Druckausg. Nesterov, Jurij Evgenʹevič Introductory lectures on convex optimization New York, N.Y. : Springer Science, 2004 ISBN 9781461346913
    Language: English
    Keywords: Konvexe Optimierung
    URL: Volltext  (lizenzpflichtig)
    URL: Cover
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    Online Resource
    Online Resource
    Boston, MA : Springer US
    UID:
    b3kat_BV042419308
    Format: 1 Online-Ressource (XVIII, 236 p)
    ISBN: 9781441988539 , 9781461346913
    Series Statement: Applied Optimization 87
    Note: It was in the middle of the 1980s, when the seminal paper by Karmarkar opened a new epoch in nonlinear optimization. The importance of this paper, containing a new polynomial-time algorithm for linear optimization problems, was not only in its complexity bound. At that time, the most surprising feature of this algorithm was that the theoretical prediction of its high efficiency was supported by excellent computational results. This unusual fact dramatically changed the style and directions of the research in nonlinear optimization. Thereafter it became more and more common that the new methods were provided with a complexity analysis, which was considered a better justification of their efficiency than computational experiments. In a new rapidly developing field, which got the name "polynomial-time interior-point methods", such a justification was obligatory. After almost fifteen years of intensive research, the main results of this development started to appear in monographs [12, 14, 16, 17, 18, 19]. Approximately at that time the author was asked to prepare a new course on nonlinear optimization for graduate students. The idea was to create a course which would reflect the new developments in the field. Actually, this was a major challenge. At the time only the theory of interior-point methods for linear optimization was polished enough to be explained to students. The general theory of self-concordant functions had appeared in print only once in the form of research monograph [12]
    Language: English
    Keywords: Konvexe Optimierung ; Berechnungskomplexität ; Einführung
    Library Location Call Number Volume/Issue/Year Availability
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