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A First Course in Optimization

Give Your Students the Proper Groundwork for Future Studies in Optimization A First Course in Optimization is designed for a one;

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Regularization Algorithms for Ill-Posed Problems

is paid to ill-posed Cauchy problems for linear operator differential equations and to ill-posed variational inequalities and optimization;

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Iterative Optimization in Inverse Problems

Iterative Optimization in Inverse Problems brings together a number of important iterative algorithms for medical imaging, optimization;

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Large-Scale Inverse Problems and Quantification of Uncertainty

optimization-based approaches to solving inverse problems. The aim is to cross-fertilize the perspectives of researchers in the areas of data;

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Computational Radiology and Imaging

methods for large linear and non-linear least-squares problems, iterative methods for linear feasibility problems, and optimization methods. The;

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Frontiers in Pde-Constrained Optimization

This volume provides a broad and uniform introduction of PDE-constrained optimization as well as to document a number of interesting and;

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Optimization in Computational Imaging and Inverse Problems

Doctoral Dissertation, University of California, San Diego, 2014. With modern optimization techniques it is generally possible to form some;

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Applications of the Topological Derivative Method

The book presents new results and applications of the topological derivative method in control theory, topology optimization and inverse;

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Inverse Problems in Engineering Mechanics III

, sensitivity analysis, optimization, material property characterization, ultrasonic non-destructive testing, elastodynamic inverse problems, thermal;

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Iterative Dynamic Programming

Dynamic programming is a powerful method for solving optimization problems, but has a number of drawbacks that limit its use to solving;

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Computational Methods for Inverse Problems in Imaging

significant features of the image. The book describes computational methods to efficiently address these problems based on new optimization algorithms;

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Computational Methods for Inverse Problems in Imaging

significant features of the image. The book describes computational methods to efficiently address these problems based on new optimization algorithms;

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Inverse Problems And Applications

in the Earth's interior, creation of astrophysical images from telescope data, finding cracks and interfaces within materials, shape optimization;

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New Trends in Parameter Identification for Mathematical Models

The Proceedings volume contains 16 contributions to the IMPA conference New Trends in Parameter Iden;...

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Algorithms for Large Scale Linear Algebraic Systems:

strategies for solving optimization problems. The most important topics dealt with concern iterative methods, especially Krylov methods, ordering;

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Dynamics of Large Structures and Inverse Problems

integrates the most recent ideas from research and industry in the field of stochastic dynamics and optimization in structural mechanics over 11;

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Inverse Problems

. The computational methods include nonsmooth optimization algorithms, direct inversion methods and uncertainty quantification via Bayesian;

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Iterative Hillclimbing Optimization Techniques

This book is a reproduction of my thesis work. An iterative hillclimbing optimization technique was introduced in this thesis. It was used;

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Computational Methods for Applied Inverse Problems

-statistical methods, e.g., regularization and optimization techniques for solving practical inverse problems.;

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Optimization in Solving Elliptic Problems

Optimization in Solving Elliptic Problems focuses on one of the most interesting and challenging problems of computational mathematics;

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Iterative Computer Algorithms With Applications In Engineering

combinatorial optimization problems: Simulated Annealing, Genetic Algorithms, Tabu Search, Simulated Evolution, and Stochastic Evolution. The authors;

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Optimization on Solution Sets of Common Fixed Point Problems

This book is devoted to a detailed study of the subgradient projection method and its variants for convex optimization problems over the;

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Optimization on Solution Sets of Common Fixed Point Problems

This book is devoted to a detailed study of the subgradient projection method and its variants for convex optimization problems over the;

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Iterative Methods In Combinatorial Optimization

With the advent of approximation algorithms for NP-hard combinatorial optimization problems, several techniques from exact optimization;

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Iterative Methods in Combinatorial Optimization

With the advent of approximation algorithms for NP-hard combinatorial optimization problems, several techniques from exact optimization;

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Mathematical Methods in Image Processing and Inverse Problems

applications were presented. The collected papers in this book also give new research trends in deep learning and optimization for imaging science. It;

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Applied Iterative Methods

algorithms. It is the first book to combine subjects such as optimization, convex analysis, and approximation theory and organize them around a;

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