Mathematical Programming, Regularization and Approximation
Author | : |
Publisher | : |
Total Pages | : 239 |
Release | : 2002 |
Genre | : Polynomials |
ISBN | : |
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Author | : |
Publisher | : |
Total Pages | : 239 |
Release | : 2002 |
Genre | : Polynomials |
ISBN | : |
Author | : Jurij S. Osipov |
Publisher | : |
Total Pages | : 239 |
Release | : 2002 |
Genre | : |
ISBN | : |
Author | : Marc Lassonde |
Publisher | : Springer Science & Business Media |
Total Pages | : 390 |
Release | : 2012-12-06 |
Genre | : Mathematics |
ISBN | : 3642575927 |
The articles in this proceedings volume reflect the current trends in the theory of approximation, optimization and mathematical economics, and include numerous applications. The book will be of interest to researchers and graduate students involved in functional analysis, approximation theory, mathematical programming and optimization, game theory, mathematical finance and economics.
Author | : Ioannis C. Demetriou |
Publisher | : Springer |
Total Pages | : 237 |
Release | : 2019-05-10 |
Genre | : Mathematics |
ISBN | : 3030127672 |
This book focuses on the development of approximation-related algorithms and their relevant applications. Individual contributions are written by leading experts and reflect emerging directions and connections in data approximation and optimization. Chapters discuss state of the art topics with highly relevant applications throughout science, engineering, technology and social sciences. Academics, researchers, data science practitioners, business analysts, social sciences investigators and graduate students will find the number of illustrations, applications, and examples provided useful. This volume is based on the conference Approximation and Optimization: Algorithms, Complexity, and Applications, which was held in the National and Kapodistrian University of Athens, Greece, June 29–30, 2017. The mix of survey and research content includes topics in approximations to discrete noisy data; binary sequences; design of networks and energy systems; fuzzy control; large scale optimization; noisy data; data-dependent approximation; networked control systems; machine learning ; optimal design; no free lunch theorem; non-linearly constrained optimization; spectroscopy.
Author | : Jurij S. Osipov |
Publisher | : |
Total Pages | : 0 |
Release | : 2002 |
Genre | : Polynomials |
ISBN | : |
Author | : Yanfei Wang |
Publisher | : Springer Science & Business Media |
Total Pages | : 354 |
Release | : 2011-06-29 |
Genre | : Mathematics |
ISBN | : 3642137423 |
"Optimization and Regularization for Computational Inverse Problems and Applications" focuses on advances in inversion theory and recent developments with practical applications, particularly emphasizing the combination of optimization and regularization for solving inverse problems. This book covers both the methods, including standard regularization theory, Fejer processes for linear and nonlinear problems, the balancing principle, extrapolated regularization, nonstandard regularization, nonlinear gradient method, the nonmonotone gradient method, subspace method and Lie group method; and the practical applications, such as the reconstruction problem for inverse scattering, molecular spectra data processing, quantitative remote sensing inversion, seismic inversion using the Lie group method, and the gravitational lensing problem. Scientists, researchers and engineers, as well as graduate students engaged in applied mathematics, engineering, geophysics, medical science, image processing, remote sensing and atmospheric science will benefit from this book. Dr. Yanfei Wang is a Professor at the Institute of Geology and Geophysics, Chinese Academy of Sciences, China. Dr. Sc. Anatoly G. Yagola is a Professor and Assistant Dean of the Physical Faculty, Lomonosov Moscow State University, Russia. Dr. Changchun Yang is a Professor and Vice Director of the Institute of Geology and Geophysics, Chinese Academy of Sciences, China.
Author | : Michel Thera |
Publisher | : Springer Science & Business Media |
Total Pages | : 281 |
Release | : 2012-12-06 |
Genre | : Business & Economics |
ISBN | : 3642457800 |
This book presents recent developments in the field of ill-posed variational problems and variational inequalities, covering a large range of theoretical, numerical and practical aspects. The main topics are: - Regularization techniques for equilibrium and fixed point problems, variational inequalities and complementary problems, - Links between approximation, penalization and regularization, - Bundle methods, nonsmooth optimization and regularization, - Error Bounds for regularized optimization problems.
Author | : Sanjeev Arora |
Publisher | : Springer |
Total Pages | : 418 |
Release | : 2003-12-15 |
Genre | : Computers |
ISBN | : 3540451986 |
This book constitutes the joint refereed proceedings of the 6th International Workshop on Approximation Algorithms for Optimization Problems, APPROX 2003 and of the 7th International Workshop on Randomization and Approximation Techniques in Computer Science, RANDOM 2003, held in Princeton, NY, USA in August 2003. The 33 revised full papers presented were carefully reviewed and selected from 74 submissions. Among the issues addressed are design and analysis of randomized and approximation algorithms, online algorithms, complexity theory, combinatorial structures, error-correcting codes, pseudorandomness, derandomization, network algorithms, random walks, Markov chains, probabilistic proof systems, computational learning, randomness in cryptography, and various applications.
Author | : Anthony V. Fiacco |
Publisher | : CRC Press |
Total Pages | : 460 |
Release | : 2020-09-24 |
Genre | : Mathematics |
ISBN | : 1000153665 |
Presents research contributions and tutorial expositions on current methodologies for sensitivity, stability and approximation analyses of mathematical programming and related problem structures involving parameters. The text features up-to-date findings on important topics, covering such areas as the effect of perturbations on the performance of algorithms, approximation techniques for optimal control problems, and global error bounds for convex inequalities.
Author | : Janos Mayer |
Publisher | : CRC Press |
Total Pages | : 174 |
Release | : 1998-02-25 |
Genre | : Computers |
ISBN | : 9789056991449 |
A computationally oriented comparison of solution algorithms for two stage and jointly chance constrained stochastic linear programming problems, this is the first book to present comparative computational results with several major stochastic programming solution approaches. The following methods are considered: regularized decomposition, stochastic decomposition and successive discrete approximation methods for two stage problems; cutting plane methods, and a reduced gradient method for jointly chance constrained problems. The first part of the book introduces the algorithms, including a unified approach to decomposition methods and their regularized counterparts. The second part addresses computer implementation of the methods, describes a testing environment based on a model management system, and presents comparative computational results with the various algorithms. Emphasis is on the computational behavior of the algorithms.