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Convex and Stochastic Optimization

Convex and Stochastic Optimization

Autorzy
Wydawnictwo Springer Nature Customer Service Center GmbH
Data wydania 01/04/2019
Wydanie Pierwsze
Liczba stron 311
Forma publikacji książka w miękkiej oprawie
Poziom zaawansowania Dla profesjonalistów, specjalistów i badaczy naukowych
Język angielski
ISBN 9783030149765
Kategorie Prawdopodobieństwo i statystyka, Optymalizacja
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Opis książki

This textbook provides an introduction to convex duality for optimization problems in Banach spaces, integration theory, and their application to stochastic programming problems in a static or dynamic setting. It introduces and analyses the main algorithms for stochastic programs, while the theoretical aspects are carefully dealt with. The reader is shown how these tools can be applied to various fields, including approximation theory, semidefinite and second-order cone programming and linear decision rules. This textbook is recommended for students, engineers and researchers who are willing to take a rigorous approach to the mathematics involved in the application of duality theory to optimization with uncertainty. "The book is mainly devoted to the theoretical study of concepts of stochastic programming. ... The book offers a solid theoretical background for researchers/students/practitioners keen on disposing of a rigorous foundation of stochastic programming." (Wim van Ackooij, Mathematical Reviews, November, 2019)

Convex and Stochastic Optimization

Spis treści

1 A convex optimization toolbox.- 2 Semidefinite and semiinfinite programming.- 3 An integration toolbox.- 4 Risk measures.- 5 Sampling and optimizing.- 6 Dynamic stochastic optimization.- 7 Markov decision processes.- 8 Algorithms.- 9 Generalized convexity and transportation theory.- References.- Index.

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