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Optimization for data analysis, Wright, Stephen J. (university Of Wisconsin, Madison) Recht, Benjamin (university Of California, Berkeley)


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Автор: Wright, Stephen J. (university Of Wisconsin, Madison) Recht, Benjamin (university Of California, Berkeley)
Название:  Optimization for data analysis
ISBN: 9781316518984
Издательство: Cambridge Academ
Классификация:





ISBN-10: 1316518981
Обложка/Формат: Hardback
Страницы: 238
Вес: 0.45 кг.
Дата издания: 21.04.2022
Серия: Mathematics
Язык: English
Издание: New ed
Иллюстрации: Worked examples or exercises; worked examples or exercises
Размер: 22.86 x 15.24 x 1.60 cm
Читательская аудитория: Tertiary education (us: college)
Ключевые слова: Data analysis: general,Data capture & analysis,Linear programming,Machine learning,Maths for engineers,Optimization, MATHEMATICS / General
Ссылка на Издательство: Link
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Поставляется из: Англии
Описание: Optimization techniques are at the core of data science. An understanding of the basic techniques and their fundamental properties provides important grounding for students, researchers, and practitioners. This compact, self-contained text covers the fundamentals of optimization algorithms, focusing on the techniques most relevant to data science.


Numerical Optimization

Автор: Nocedal, Jorge.
Название: Numerical Optimization
ISBN: 0387303030 ISBN-13(EAN): 9780387303031
Издательство: Springer
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Цена: 10662.00 р.
Наличие на складе: Заказано в издательстве.

Описание: Optimization is an important tool used in decision science and for the analysis of physical systems used in engineering. It begins with very simple ideas progressing through more complicated concepts, concentrating on methods for both unconstrained and constrained optimization.

Beyond the Worst-Case Analysis of Algorithms

Автор: Tim Roughgarden
Название: Beyond the Worst-Case Analysis of Algorithms
ISBN: 1108494315 ISBN-13(EAN): 9781108494311
Издательство: Cambridge Academ
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Цена: 9187.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Understanding when and why algorithms work is a fundamental challenge. For problems ranging from clustering to linear programming to neural networks there are significant gaps between empirical performance and prediction based on traditional worst-case analysis. The book introduces exciting new methods for assessing algorithm performance.

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: 26024.00 р.
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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
Optimization and Data Analysis in Biomedical Informatics

Автор: Panos M. Pardalos; Thomas F. Coleman; Petros Xanth
Название: Optimization and Data Analysis in Biomedical Informatics
ISBN: 1489999663 ISBN-13(EAN): 9781489999665
Издательство: Springer
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Цена: 15372.00 р.
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Описание: This work is targeted to applied mathematicians, computer scientists, industrial engineers, and clinical scientists who are interested in exploring emerging and fascinating interdisciplinary topics of research.

Optimization Techniques for Problem Solving in Uncertainty

Автор: Surafel Luleseged Tilahun, Jean Medard T. Ngnotchouye
Название: Optimization Techniques for Problem Solving in Uncertainty
ISBN: 1522550917 ISBN-13(EAN): 9781522550914
Издательство: Mare Nostrum (Eurospan)
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Цена: 28413.00 р.
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Описание: When it comes to optimization techniques, in some cases, the available information from real models may not be enough to construct either a probability distribution or a membership function for problem solving. In such cases, there are various theories that can be used to quantify the uncertain aspects.Optimization Techniques for Problem Solving in Uncertainty is a scholarly reference resource that looks at uncertain aspects involved in different disciplines and applications. Featuring coverage on a wide range of topics including uncertain preference, fuzzy multilevel programming, and metaheuristic applications, this book is geared towards engineers, managers, researchers, and post-graduate students seeking emerging research in the field of optimization.

Open Problems in Optimization and Data Analysis

Автор: Panos M. Pardalos; Athanasios Migdalas
Название: Open Problems in Optimization and Data Analysis
ISBN: 3319991418 ISBN-13(EAN): 9783319991412
Издательство: Springer
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Цена: 13974.00 р.
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Описание: Computational and theoretical open problems in optimization, computational geometry, data science, logistics, statistics, supply chain modeling, and data analysis are examined in this book. Each contribution provides the fundamentals needed to fully comprehend the impact of individual problems. Current theoretical, algorithmic, and practical methods used to circumvent each problem are provided to stimulate a new effort towards innovative and efficient solutions. Aimed towards graduate students and researchers in mathematics, optimization, operations research, quantitative logistics, data analysis, and statistics, this book provides a broad comprehensive approach to understanding the significance of specific challenging or open problems within each discipline. The contributions contained in this book are based on lectures focused on “Challenges and Open Problems in Optimization and Data Science” presented at the Deucalion Summer Institute for Advanced Studies in Optimization, Mathematics, and Data Science in August 2016.

Sparse Solutions of Underdetermined Linear Systems

Автор: Ming-Jun Lai, Yang Wang
Название: Sparse Solutions of Underdetermined Linear Systems
ISBN: 1611976502 ISBN-13(EAN): 9781611976502
Издательство: Mare Nostrum (Eurospan)
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Цена: 11161.00 р.
Наличие на складе: Нет в наличии.

Описание: This textbook presents a special solution of underdetermined linear systems where the number of nonzero entries in the solution is very small compared to the total number of entries. This is called sparse solution. As underdetermined linear systems can be very different, the authors explain how to compute a sparse solution by many approaches.Sparse Solutions of Underdetermined Linear Systems:Contains 72 algorithms for finding sparse solutions of underdetermined linear systems and their applications for matrix completion, graph clustering, and phase retrieval.Provides a detailed explanation of these algorithms including derivations and convergence analysis.Includes exercises for each chapter to help the reader understand the material.This textbook is appropriate for graduate students in math and applied math, computer science, statistics, data science, and engineering. Advisors and postdocs will also find the book of interest.It is appropriate for the following courses: Advanced Numerical Analysis, Special Topics on Numerical Analysis, Topics on Data Science, Topics on Numerical Optimization, and Topics on Approximation Theory.

Mathematical Pictures at a Data Science Exhibition

Автор: Foucart Simon
Название: Mathematical Pictures at a Data Science Exhibition
ISBN: 1316518884 ISBN-13(EAN): 9781316518885
Издательство: Cambridge University Press
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Цена: 20714.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This text explores a diverse set of data science topics through a mathematical lens, helping mathematicians become acquainted with data science in general, and machine learning, optimal recovery, compressive sensing, optimization, and neural networks in particular. It will also be valuable to data scientists seeking mathematical sophistication.


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