Optimality Conditions in Convex Optimization, Dhara, Anulekha

Автор: Hazan, Elad
Название: Introduction to online convex optimization, second edition
ISBN: 0262046989 ISBN-13(EAN): 9780262046985
Издательство: MIT Press
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Цена: 74130.00 T
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Описание: The Diesel That Did It tells the story of the legendary diesel-electric locomotive, the FT.

Название: Selected Applications of Convex Optimization
ISBN: 3662463555 ISBN-13(EAN): 9783662463550
Издательство: Springer
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Цена: 46570.00 T
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Описание: This book focuses on the applications of convex optimization and highlights several topics, including support vector machines, parameter estimation, norm approximation and regularization, semi-definite programming problems, convex relaxation, and geometric problems.

Название: Pareto optimality, game theory and equilibria
ISBN: 0387772464 ISBN-13(EAN): 9780387772462
Издательство: Springer
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Цена: 213360.00 T
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Описание: This comprehensive work examines important recent developments and modern applications in the fields of optimization, control, game theory and equilibrium programming. The book consists of 29 survey chapters written by distinguished researchers.

Автор: G.I.N. Rozvany
Название: Shape and Layout Optimization of Structural Systems and Optimality Criteria Methods
ISBN: 3211823638 ISBN-13(EAN): 9783211823637
Издательство: Springer
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Цена: 81050.00 T
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Описание: This examination of shape and layout optimation for structural design problems also describes new optimality criteria methods which are capable of handling many thousands of design variables and active design constraints.

Автор: M. Save; W. Prager
Название: Structural Optimization
ISBN: 1461579236 ISBN-13(EAN): 9781461579236
Издательство: Springer
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Цена: 46570.00 T
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Автор: A.V. Arutyunov
Название: Optimality Conditions: Abnormal and Degenerate Problems
ISBN: 0792366557 ISBN-13(EAN): 9780792366553
Издательство: Springer
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Цена: 102480.00 T
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Описание: Devoted to the necessary and sufficient extremality conditions. This book studies the abstract minimization problem with constraints. It features a chapter devoted to the optimal control problem. It studies the integral quadratic form. It discusses the local properties of smooth nonlinear mappings in a neighbourhood of an abnormal point.

Автор: Hernandez-Lerma
Название: Discrete-Time Markov Control Processes
ISBN: 0387945792 ISBN-13(EAN): 9780387945798
Издательство: Springer
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Цена: 121110.00 T
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Описание: This text provides a unified treatment of some recent theoretical developments on Markov control processes. Interest is mainly confined to MCPs with Borel state and control spaces, and possibly unbound costs and non-compact control constraint sets.

Автор: Haya Shajaiah; Ahmed Abdelhadi; Charles Clancy
Название: Resource Allocation with Carrier Aggregation in Cellular Networks
ISBN: 3319605399 ISBN-13(EAN): 9783319605395
Издательство: Springer
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Цена: 130430.00 T
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Описание: This book introduces an efficient resource management approach for future spectrum sharing systems. The book focuses on providing an optimal resource allocation framework based on carrier aggregation to allocate multiple carriers` resources efficiently among mobile users.

Автор: Freddy Delbaen; Mikl?s R?sonyi; Christophe Stricke
Название: Optimality and Risk - Modern Trends in Mathematical Finance
ISBN: 3642026079 ISBN-13(EAN): 9783642026072
Издательство: Springer
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Цена: 93160.00 T
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Описание: Yuri Kabanov is one of the leading figures in mathematical finance. To mark his 60th birthday, this book pays tribute to his achievements in this area and in probability in general. The volume gives a fair overview of these topics and the current approaches.

Автор: Michael Carlberg; Arne Hansen
Название: Sustainability and Optimality of Public Debt
ISBN: 3642329667 ISBN-13(EAN): 9783642329661
Издательство: Springer
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Цена: 93160.00 T
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Описание: Using the Solow model, the overlapping general generations model and the infinite horizons model, this book explores the sustainability and optimality of public debt under three scenarios: the closed economy, the small open economy, and a two-country setting.

Автор: Haya Shajaiah; Ahmed Abdelhadi; Charles Clancy
Название: Resource Allocation with Carrier Aggregation in Cellular Networks
ISBN: 3319868829 ISBN-13(EAN): 9783319868820
Издательство: Springer
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Цена: 130430.00 T
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Описание: This book introduces an efficient resource management approach for future spectrum sharing systems. The book focuses on providing an optimal resource allocation framework based on carrier aggregation to allocate multiple carriers’ resources efficiently among mobile users. Furthermore, it provides an optimal traffic dependent pricing mechanism that could be used by network providers to charge mobile users for the allocated resources. The book provides different resource allocation with carrier aggregation solutions, for different spectrum sharing scenarios, and compares them. The provided solutions consider the diverse quality of experience requirement of multiple applications running on the user’s equipment since different applications require different application performance. In addition, the book addresses the resource allocation problem for spectrum sharing systems that require user discrimination when allocating the network resources.

Автор: Juditsky Anatoli, Nemirovski Arkadi
Название: Statistical Inference Via Convex Optimization
ISBN: 0691197296 ISBN-13(EAN): 9780691197296
Издательство: Wiley
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Цена: 92930.00 T
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Описание:

This authoritative book draws on the latest research to explore the interplay of high-dimensional statistics with optimization. Through an accessible analysis of fundamental problems of hypothesis testing and signal recovery, Anatoli Juditsky and Arkadi Nemirovski show how convex optimization theory can be used to devise and analyze near-optimal statistical inferences.

Statistical Inference via Convex Optimization is an essential resource for optimization specialists who are new to statistics and its applications, and for data scientists who want to improve their optimization methods. Juditsky and Nemirovski provide the first systematic treatment of the statistical techniques that have arisen from advances in the theory of optimization. They focus on four well-known statistical problems--sparse recovery, hypothesis testing, and recovery from indirect observations of both signals and functions of signals--demonstrating how they can be solved more efficiently as convex optimization problems. The emphasis throughout is on achieving the best possible statistical performance. The construction of inference routines and the quantification of their statistical performance are given by efficient computation rather than by analytical derivation typical of more conventional statistical approaches. In addition to being computation-friendly, the methods described in this book enable practitioners to handle numerous situations too difficult for closed analytical form analysis, such as composite hypothesis testing and signal recovery in inverse problems.

Statistical Inference via Convex Optimization features exercises with solutions along with extensive appendixes, making it ideal for use as a graduate text.