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Foundations of Applied Mathematics, Volume 2: Algorithms, Approximation, Optimization, Jeffrey Humpherys, Tyler J. Jarvis


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Автор: Jeffrey Humpherys, Tyler J. Jarvis
Название:  Foundations of Applied Mathematics, Volume 2: Algorithms, Approximation, Optimization
ISBN: 9781611976052
Издательство: Mare Nostrum (Eurospan)
Классификация:




ISBN-10: 1611976057
Обложка/Формат: Hardback
Страницы: 820
Вес: 1.84 кг.
Дата издания: 30.05.2020
Серия: Mathematics
Язык: English
Размер: 181 x 255 x 24
Читательская аудитория: Professional and scholarly
Ключевые слова: Applied mathematics,Functional analysis & transforms,Mathematical theory of computation,Optimization,Probability & statistics
Подзаголовок: Algorithms, approximation, optimization
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Поставляется из: Англии
Описание: In this second book of what will be a four-volume series, the authors present, in a mathematically rigorous way, the essential foundations of both the theory and practice of algorithms, approximation, and optimization—essential topics in modern applied and computational mathematics. This material is the introductory framework upon which algorithm analysis, optimization, probability, statistics, machine learning, and control theory are built. This text gives a unified treatment of several topics that do not usually appear together: the theory and analysis of algorithms for mathematicians and data science students; probability and its applications; the theory and applications of approximation, including Fourier series, wavelets, and polynomial approximation; and the theory and practice of optimization, including dynamic optimization.When used in concert with the free supplemental lab materials, Foundations of Applied Mathematics, Volume 2: Algorithms, Approximation, Optimization teaches not only the theory but also the computational practice of modern mathematical methods. Exercises and examples build upon each other in a way that continually reinforces previous ideas, allowing students to retain learned concepts while achieving a greater depth. The mathematically rigorous lab content guides students to technical proficiency and answers the age-old question “When am I going to use this?”This textbook is geared toward advanced undergraduate and beginning graduate students in mathematics, data science, or machine learning.
Дополнительное описание: Applied mathematics|Mathematical theory of computation|Probability and statistics|Optimization|Functional analysis and transforms


Inverse Problems: Tikhonov Theory and Algorithms

Автор: Ito Kazufumi, Jin Bangti
Название: Inverse Problems: Tikhonov Theory and Algorithms
ISBN: 9814596191 ISBN-13(EAN): 9789814596190
Издательство: World Scientific Publishing
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Цена: 118270.00 T
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Описание:

Inverse problems arise in practical applications whenever one needs to deduce unknowns from observables. This monograph is a valuable contribution to the highly topical field of computational inverse problems. Both mathematical theory and numerical algorithms for model-based inverse problems are discussed in detail. The mathematical theory focuses on nonsmooth Tikhonov regularization for linear and nonlinear inverse problems. The computational methods include nonsmooth optimization algorithms, direct inversion methods and uncertainty quantification via Bayesian inference.

The book offers a comprehensive treatment of modern techniques, and seamlessly blends regularization theory with computational methods, which is essential for developing accurate and efficient inversion algorithms for many practical inverse problems.

It demonstrates many current developments in the field of computational inversion, such as value function calculus, augmented Tikhonov regularization, multi-parameter Tikhonov regularization, semismooth Newton method, direct sampling method, uncertainty quantification and approximate Bayesian inference. It is written for graduate students and researchers in mathematics, natural science and engineering.


Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques

Автор: Sanjeev Arora; Klaus Jansen; Jose D.P. Rolim; Amit
Название: Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques
ISBN: 3540407707 ISBN-13(EAN): 9783540407706
Издательство: Springer
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Цена: 69870.00 T
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Introduction to the Foundations of Applied Mathematics

Автор: Holmes
Название: Introduction to the Foundations of Applied Mathematics
ISBN: 0387877495 ISBN-13(EAN): 9780387877495
Издательство: Springer
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Цена: 55890.00 T
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Описание: This book deals with the construction, analysis and interpretation of mathematical models to help us understand the world. It develops the mathematical and physical ideas that are fundamental in understanding contemporary problems in science and engineering.

Approximation Of Set-Valued Functions: Adaptation Of Classical Approximation Operators

Автор: Dyn Nira Et Al
Название: Approximation Of Set-Valued Functions: Adaptation Of Classical Approximation Operators
ISBN: 1783263024 ISBN-13(EAN): 9781783263028
Издательство: World Scientific Publishing
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Цена: 74970.00 T
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This book is aimed at the approximation of set-valued functions with compact sets in an Euclidean space as values. The interest in set-valued functions is rather new. Such functions arise in various modern areas such as control theory, dynamical systems and optimization. The authors' motivation also comes from the newer field of geometric modeling, in particular from the problem of reconstruction of 3D objects from 2D cross-sections. This is reflected in the focus of this book, which is the approximation of set-valued functions with general (not necessarily convex) sets as values, while previous results on this topic are mainly confined to the convex case. The approach taken in this book is to adapt classical approximation operators and to provide error estimates in terms of the regularity properties of the approximated set-valued functions. Specialized results are given for functions with 1D sets as values.


MM Optimization Algorithms

Автор: Kenneth Lange
Название: MM Optimization Algorithms
ISBN: 1611974399 ISBN-13(EAN): 9781611974393
Издательство: Mare Nostrum (Eurospan)
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Цена: 68130.00 T
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Описание: Offers an overview of the MM principle, a device for deriving optimization algorithms satisfying the ascent or descent property. These algorithms can:Separate the variables of a problem. Avoid large matrix inversions. Linearize a problem. Restore symmetry.Deal with equality and inequality constraints gracefully. Turn a non-differentiable problem into a smooth problem.The author: Presents the first extended treatment of MM algorithms, which are ideal for high-dimensional optimization problems in data mining, imaging, and genomics. Derives numerous algorithms from a broad diversity of application areas, with a particular emphasis on statistics, biology, and data mining.Summarizes a large amount of literature that has not reached book form before.

Advances and Trends in Optimization with Engineering Applications

Автор: Tamas Terlaky and Miguel F. Anjos
Название: Advances and Trends in Optimization with Engineering Applications
ISBN: 1611974674 ISBN-13(EAN): 9781611974676
Издательство: Mare Nostrum (Eurospan)
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Цена: 101640.00 T
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Описание: Optimization is of critical importance in engineering. This overview of state-of-the-art optimization techniques reviews 10 major areas of optimization and related engineering applications. It provides a solid foundation for engineers and mathematical optimizers alike who want to understand not only the importance of optimization methods to engineering but also the capabilities of current methods.

Approximation Algorithms for Combinatorial Optimization

Автор: Klaus Jansen; Stefano Leonardi; Vijay Vazirani
Название: Approximation Algorithms for Combinatorial Optimization
ISBN: 3540441867 ISBN-13(EAN): 9783540441861
Издательство: Springer
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Цена: 65210.00 T
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Описание: Compiled from the proceedings of the 5th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, this volume contains 20 revised full papers. Coverage includes design and analysis of approximation algorithms, inapproximability results and online problems.

Topological Optimization and Optimal Transport: In the Applied Sciences

Автор: Maitine Bergounioux, ?douard Oudet, Martin Rumpf,
Название: Topological Optimization and Optimal Transport: In the Applied Sciences
ISBN: 3110439263 ISBN-13(EAN): 9783110439267
Издательство: Walter de Gruyter
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Цена: 173490.00 T
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Описание:

By discussing topics such as shape representations, relaxation theory and optimal transport, trends and synergies of mathematical tools required for optimization of geometry and topology of shapes are explored. Furthermore, applications in science and engineering, including economics, social sciences, biology, physics and image processing are covered.

Contents
Part I

  • Geometric issues in PDE problems related to the infinity Laplace operator
  • Solution of free boundary problems in the presence of geometric uncertainties
  • Distributed and boundary control problems for the semidiscrete Cahn-Hilliard/Navier-Stokes system with nonsmooth Ginzburg-Landau energies
  • High-order topological expansions for Helmholtz problems in 2D
  • On a new phase field model for the approximation of interfacial energies of multiphase systems
  • Optimization of eigenvalues and eigenmodes by using the adjoint method
  • Discrete varifolds and surface approximation

Part II

  • Weak Monge-Ampere solutions of the semi-discrete optimal transportation problem
  • Optimal transportation theory with repulsive costs
  • Wardrop equilibria: long-term variant, degenerate anisotropic PDEs and numerical approximations
  • On the Lagrangian branched transport model and the equivalence with its Eulerian formulation
  • On some nonlinear evolution systems which are perturbations of Wasserstein gradient flows
  • Pressureless Euler equations with maximal density constraint: a time-splitting scheme
  • Convergence of a fully discrete variational scheme for a thin-film equatio
  • Interpretation of finite volume discretization schemes for the Fokker-Planck equation as gradient flows for the discrete Wasserstein distance

Approximation Algorithms for Combinatorial Optimization

Автор: Klaus Jansen; Jose Rolim
Название: Approximation Algorithms for Combinatorial Optimization
ISBN: 3540647368 ISBN-13(EAN): 9783540647362
Издательство: Springer
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Цена: 65210.00 T
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Описание: A volume of 17 papers from a workshop on approximation algorithms for combinatorial optimization. They address the design and analysis of approximation algorithms, inapproximability results, on-line problems, randomization techniques, average-case analysis, scheduling problems, and applications.

Randomization, Approximation, and Combinatorial Optimization. Algorithms and Techniques

Автор: Dorit Hochbaum; Klaus Jansen; Jose D.P. Rolim; Ali
Название: Randomization, Approximation, and Combinatorial Optimization. Algorithms and Techniques
ISBN: 3540663290 ISBN-13(EAN): 9783540663294
Издательство: Springer
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Цена: 65210.00 T
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Описание: This text presents various new results within the areas covered by the workshop.

Mathematical Methods in Engineering

Автор: Powers, Joseph M. (University of Notre Dame, Indiana) Sen, Mihir (University of Notre Dame, Indiana)
Название: Mathematical Methods in Engineering
ISBN: 1107037042 ISBN-13(EAN): 9781107037045
Издательство: Cambridge Academ
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Цена: 67590.00 T
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Описание: This book is designed for engineering graduate students. It connects mathematics to a variety of methods used for engineering problems by walking the reader stepwise through examples that have been worked in detail, followed by numerous homework problems to reinforce learning and connect the subject matter to engineering applications.

Recursion Theory: Computational Aspects of Definability

Автор: Chi Tat Chong, Liang Yu
Название: Recursion Theory: Computational Aspects of Definability
ISBN: 3110275554 ISBN-13(EAN): 9783110275551
Издательство: Walter de Gruyter
Цена: 138080.00 T
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Описание: This monograph presents recursion theory from a generalized point of view centered on the computational aspects of definability. A major theme is the study of the structures of degrees arising from two key notions of reducibility, the Turing degrees and the hyperdegrees, using techniques and ideas from recursion theory, hyperarithmetic theory, and descriptive set theory.The emphasis is on the interplay between recursion theory and set theory, anchored on the notion of definability. The monograph covers a number of fundamental results in hyperarithmetic theory as well as some recent results on the structure theory of Turing and hyperdegrees. It also features a chapter on the applications of these investigations to higher randomness.


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