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  • Introduction to Global Optimization Exploiting Space-Filling Curves

    Series series Mathematics and Statistics (R0)
    Introduction to Global Optimization Exploiting Space-Filling Curves provides an overview of classical and new results pertaining to the usage of space-filling curves in global optimization. The authors look at a family of derivative-free numerical algorithms applying space-filling curves to reduce the dimensionality of the global optimization problem; along with a number of unconventional ideas, ... Read more

    $53.99 USD

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    Riemannian, Contact, Symplectic

    Series series Mathematics and Statistics (R0)
    Differential geometry arguably offers the smoothest transition from the standard university mathematics sequence of the first four semesters in calculus, linear algebra, and differential equations to the higher levels of abstraction and proof encountered at the upper division by mathematics majors. Today it is possible to describe differential geometry as "the study of structures on the tangent ... Read more

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  • Introduction to Experimental Mathematics

    Series series Cambridge Mathematical Textbooks
    Mathematics is not, and never will be, an empirical science, but mathematicians are finding that the use of computers and specialized software allows the generation of mathematical insight in the form of conjectures and examples, which pave the way for theorems and their proofs. In this way, the experimental approach to pure mathematics is revolutionizing the way research mathematicians work. As ... Read more

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  • Topics in Physical Mathematics

    Series series Mathematics and Statistics (R0)
    As many readers will know, the 20th century was a time when the fields of mathematics and the sciences were seen as two separate entities. Caused by the rapid growth of the physical sciences and an increasing abstraction in mathematical research, each party, physicists and mathematicians alike, suffered a misconception; not only of the opposition’s theoretical underpinning, but of how the two ... Read more

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  • Gems of Combinatorial Optimization and Graph Algorithms

    Are you looking for new lectures for your course on algorithms, combinatorial optimization, or algorithmic game theory? Maybe you need a convenient source of relevant, current topics for a graduate student or advanced undergraduate student seminar? Or perhaps you just want an enjoyable look at some beautiful mathematical and algorithmic results, ideas, proofs, concepts, and techniques in discrete ... Read more

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  • Numerical Analysis Using Sage

    Series series Mathematics and Statistics (R0)
    This is the first numerical analysis text to use Sage for the implementation of algorithms and can be used in a one-semester course for undergraduates in mathematics, math education, computer science/information technology, engineering, and physical sciences. The primary aim of this text is to simplify understanding of the theories and ideas from a numerical analysis/numerical methods course via a ... Read more

    $49.99 USD

  • Integer Programming

    Series series Mathematics and Statistics (R0)
    This book is an elegant and rigorous presentation of integer programming, exposing the subject’s mathematical depth and broad applicability. Special attention is given to the theory behind the algorithms used in state-of-the-art solvers. An abundance of concrete examples and exercises of both theoretical and real-world interest explore the wide range of applications and ramifications of the theory ... Read more

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  • Numerical Methods in Matrix Computations

    by Åke Björck ...
    Series series Mathematics and Statistics (R0)
    Matrix algorithms are at the core of scientific computing and are indispensable tools in most applications in engineering. This book offers a comprehensive and up-to-date treatment of modern methods in matrix computation. It uses a unified approach to direct and iterative methods for linear systems, least squares and eigenvalue problems. A thorough analysis of the stability, accuracy, and ... Read more

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  • Polyhedral and Algebraic Methods in Computational Geometry

    Series series Mathematics and Statistics (R0)
    Polyhedral and Algebraic Methods in Computational Geometry provides a thorough introduction into algorithmic geometry and its applications. It presents its primary topics from the viewpoints of discrete, convex and elementary algebraic geometry.The first part of the book studies classical problems and techniques that refer to polyhedral structures. The authors include a study on algorithms for ... Read more

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  • Eigenvalue Problems: Algorithms, Software and Applications in Petascale Computing

    EPASA 2015, Tsukuba, Japan, September 2015

    Series series Springer Nature Proceedings excluding Computer Science
    This book provides state-of-the-art and interdisciplinary topics on solving matrix eigenvalue problems, particularly by using recent petascale and upcoming post-petascale supercomputers. It gathers selected topics presented at the International Workshops on Eigenvalue Problems: Algorithms; Software and Applications, in Petascale Computing (EPASA2014 and EPASA2015), which brought together leading ... Read more

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  • Shape Reconstruction from Apparent Contours

    Theory and Algorithms

    Series series Computer Science (R0)
    Motivated by a variational model concerning the depth of the objects in a picture and the problem of hidden and illusory contours, this book investigates one of the central problems of computer vision: the topological and algorithmic reconstruction of a smooth three dimensional scene starting from the visible part of an apparent contour.The authors focus their attention on the manipulation of ... Read more

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  • Matrix-Analytic Methods in Stochastic Models

    Series series Springer Nature Proceedings excluding Computer Science
    Matrix-analytic and related methods have become recognized as an important and fundamental approach for the mathematical analysis of general classes of complex stochastic models. Research in the area of matrix-analytic and related methods seeks to discover underlying probabilistic structures intrinsic in such stochastic models, develop numerical algorithms for computing functionals (e.g., ... Read more

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