£46.83

Springer Convex and Stochastic Optimization (Universitext) Book

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Description

Master complex mathematical concepts with Convex and Stochastic Optimization from Springer. This textbook provides a comprehensive introduction to convex duality for optimization problems in Banach spaces and integration theory. It is designed to help you understand the application of these theories to stochastic programming problems in both static and dynamic settings. This resource introduces and analyzes the main algorithms used for stochastic programs while ensuring all theoretical aspects are handled with care. You will learn how to apply these mathematical tools to diverse fields such as approximation theory, semidefinite programming, second-order cone programming, and linear decision rules. Whether you are a student, an engineer, or a researcher, this book offers the depth required to navigate advanced optimization challenges. It serves as a practical guide for those looking to bridge the gap between theoretical mathematical frameworks and real-world applications in applied mathematics.

Key Features

Covers convex duality for optimization problems within Banach spaces and integration theory.

Explains applications to stochastic programming problems in both static and dynamic settings.

Provides a detailed analysis of the main algorithms used for stochastic programs.

Includes practical applications for approximation theory and linear decision rules.

Addresses specialized topics like semidefinite and second-order cone programming.

Designed for students, engineers, and researchers in the field of applied mathematics.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
29 April 2019
Listed Since
06 February 2019

Barcode

No barcode data available

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