Stochastic Approximation and Recursive Algorithms and Applications, Harold Kushner; G. George Yin
Автор: Oleg B. Lupanov; Oktay M. Kasim-Zade; Alexander V. Название: Stochastic Algorithms: Foundations and Applications ISBN: 3540294988 ISBN-13(EAN): 9783540294986 Издательство: Springer Рейтинг: Цена: 9083.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Constitutes the refereed proceedings of the Third International Symposium on Stochastic Algorithms: Foundations and Applications, SAGA 2005, held in Moscow, Russia in October 2005. This title includes papers that cover both theoretical as well as applied aspects of stochastic computations with a special focus on the algorithmic ideas.
Автор: Juraj Hromkovi?; Richard Kr?lovi?; Marc Nunkesser; Название: Stochastic Algorithms: Foundations and Applications ISBN: 3540748709 ISBN-13(EAN): 9783540748700 Издательство: Springer Рейтинг: Цена: 9083.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Constitutes the proceedings of the 4th International Symposium on Stochastic Algorithms: Foundations and Applications, SAGA 2007, held in Zurich, Switzerland, in September 2007. This book covers theoretical as well as applied aspects of stochastic computations with a focus on investigating the power of randomization in algorithmics.
Автор: Asmussen Название: Stochastic Simulation: Algorithms and Analysis ISBN: 038730679X ISBN-13(EAN): 9780387306797 Издательство: Springer Рейтинг: Цена: 6981.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Sampling-based computational methods have become a fundamental part of the numerical toolset of practitioners and researchers across an enormous number of different applied domains and academic disciplines. This book provides a broad treatment of such sampling-based methods , as well as accompanying mathematical analysis of the convergence properties of the methods discussed . The reach of the ideas is illustrated by discussing a wide range of applications and the models that have found wide usage. The first half of the book focusses on general methods, whereas the second half discusses model-specific algorithms. Given the wide range of examples, exercises and applications students, practitioners and researchers in probability, statistics, operations research, economics, finance, engineering as well as biology and chemistry and physics will find the book of value. Soren Asmussen is Professor of Applied Probability at Aarhus University, Denmark and Peter Glynn is Thomas Ford Professor of Engineering at Stanford University.
Автор: Mark Burgin Название: Super-Recursive Algorithms ISBN: 1441930604 ISBN-13(EAN): 9781441930606 Издательство: Springer Рейтинг: Цена: 23058.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
* The first exposition on super-recursive algorithms, systematizing all main classes and providing an accessible, focused examination of the theory and its ramifications
* Demonstrates how these algorithms are more appropriate as mathematical models for modern computers and how they present a better framework for computing methods
* Develops a new practically-oriented perspective on the theory of algorithms, computation, and automata, as a whole
Автор: Wolfgang H?rdle; Gerard Kerkyacharian; Dominique P Название: Wavelets, Approximation, and Statistical Applications ISBN: 0387984534 ISBN-13(EAN): 9780387984537 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The mathematical theory of ondelettes (wavelets) was developed by Yves Meyer and many collaborators about 10 years ago. Five years ago wavelet theory progressively appeared to be a power- ful framework for nonparametric statistical problems.
Автор: G?rtner, Matousek Название: Approximation Algorithms and Semidefinite Programming ISBN: 3642220142 ISBN-13(EAN): 9783642220142 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Semidefinite programs constitute one of the largest classes of optimization problems that can be solved with reasonable efficiency - both in theory and practice. They play a key role in a variety of research areas, such as combinatorial optimization, approximation algorithms, computational complexity, graph theory, geometry, real algebraic geometry and quantum computing. This book is an introduction to selected aspects of semidefinite programming and its use in approximation algorithms. It covers the basics but also a significant amount of recent and more advanced material. There are many computational problems, such as MAXCUT, for which one cannot reasonably expect to obtain an exact solution efficiently, and in such case, one has to settle for approximate solutions. For MAXCUT and its relatives, exciting recent results suggest that semidefinite programming is probably the ultimate tool. Indeed, assuming the Unique Games Conjecture, a plausible but as yet unproven hypothesis, it was shown that for these problems, known algorithms based on semidefinite programming deliver the best possible approximation ratios among all polynomial-time algorithms. This book follows the “semidefinite side” of these developments, presenting some of the main ideas behind approximation algorithms based on semidefinite programming. It develops the basic theory of semidefinite programming, presents one of the known efficient algorithms in detail, and describes the principles of some others. It also includes applications, focusing on approximation algorithms.
Автор: Emmanuil H Georgoulis; Armin Iske; Jeremy Levesley Название: Approximation Algorithms for Complex Systems ISBN: 3642266657 ISBN-13(EAN): 9783642266652 Издательство: Springer Рейтинг: Цена: 29209.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Part I INVITED SURVEYS: Emergent Behaviour in Large Electrical Networks by D. P. Almond, C.J. Budd, N.J. McCullen.- Algorithms and Error Bounds for Multivariate Piecewise Constant Approximation by O. Davydov.- Anisotropic Triangulation Methods in Adaptive Image Approximation by L. Demaret, A. Iske.- Form Assessment in Coordinate Metrology by A.B. Forbes and H.D.Minh.- Discontinuous Galerkin Methods for Linear Problems: An Introduction by E. H. Georgoulis.- A Numerical Analyst's View of the Lattice Boltzmann Method by A. G. Gorban, J. Levesley, D. Packwood.- Approximating Probability Measures on Manifolds via Radial Basis Functions by J. Levesley, X. Sun.- Part II CONTRIBUTED RESEARCH PAPERS: Modelling Clinical Decay Data Using Exponential Functions by M.G. Cox.- Towards Calculating the Basin of Attraction of Non-Smooth Dynamical Systems Using Radial Basis Functions by P. Giesl.- Stabilizing Lattice Boltzmann Simulation of Fluid Flow past a Circular Cylinder with Ehrenfests' Limiter by T.S. Khan, J. Levesley.- Fast and Stable Interpolation of Well Data Using the Norm Function by B. Li, J. Levesley.- Algorithms and Literate Programs for Weighted Low-Rank Approximation with Missing Data by I. Markovsky.- On Bivariate Interpolatory Mask Symbols, Subdivision and Refinable Functions by A. F. Rabarison, J. de Villiers.- Model and Feature Selection in Metrology Data Approximation by X. Yang, A. B. Forbes.
Автор: Micka?l D. Chekroun; Honghu Liu; Shouhong Wang Название: Approximation of Stochastic Invariant Manifolds ISBN: 3319124951 ISBN-13(EAN): 9783319124957 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This first volume is concerned with the analytic derivation of explicit formulas for the leading-order Taylor approximations of (local) stochastic invariant manifolds associated with a broad class of nonlinear stochastic partial differential equations.
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