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|a 9783319137100
|9 978-3-319-13710-0
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|a 10.1007/978-3-319-13710-0
|2 doi
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|a Peypouquet, Juan.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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|a Convex Optimization in Normed Spaces
|h [electronic resource] :
|b Theory, Methods and Examples /
|c by Juan Peypouquet.
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|a 1st ed. 2015.
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2015.
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|a XIV, 124 p. 17 illus.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
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|2 rdamedia
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|a online resource
|b cr
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|a text file
|b PDF
|2 rda
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|a SpringerBriefs in Optimization,
|x 2191-575X ;
|v 0
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|a Basic Functional Analysis -- Existence of Minimizers -- Convex Analysis and Subdifferential Calculus -- Examples -- Problem-solving Strategies -- Keynote Iterative Methods.
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|a This work is intended to serve as a guide for graduate students and researchers who wish to get acquainted with the main theoretical and practical tools for the numerical minimization of convex functions on Hilbert spaces. Therefore, it contains the main tools that are necessary to conduct independent research on the topic. It is also a concise, easy-to-follow and self-contained textbook, which may be useful for any researcher working on related fields, as well as teachers giving graduate-level courses on the topic. It will contain a thorough revision of the extant literature including both classical and state-of-the-art references.
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|a Mathematical optimization.
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|a Calculus of variations.
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|a Algorithms.
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|a Calculus of Variations and Optimization.
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|a Algorithms.
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710 |
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|a SpringerLink (Online service)
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|t Springer Nature eBook
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|i Printed edition:
|z 9783319137117
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|i Printed edition:
|z 9783319137094
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|a SpringerBriefs in Optimization,
|x 2191-575X ;
|v 0
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|u https://doi.uam.elogim.com/10.1007/978-3-319-13710-0
|z Texto Completo
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|a ZDB-2-SMA
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|a ZDB-2-SXMS
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|a Mathematics and Statistics (SpringerNature-11649)
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|a Mathematics and Statistics (R0) (SpringerNature-43713)
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