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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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Real-Time PDE-Constrained Optimization

difficulties. A particularly challenging class of PDE-constrained optimization problems is characterized by the need for real-time solution, i.e;

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Constrained Optimization and Optimal Control for Partial Differential Equations

optimization for PDE-constrained problems has undergone a dramatic increase of interest during the last four decades, a full theory for nonlinear;

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Alternating Direction Method of Multipliers for Machine Learning

Machine learning heavily relies on optimization algorithms to solve its learning models. Constrained problems constitute a major type;

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Mesh Dependence in PDE Constrained Optimisation

This book provides an introduction to PDE-constrained optimisation using finite elements and the adjoint approach. The practical impact;

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Evolutionary Constrained Optimization

This book makes available a self-contained collection of modern research addressing the general constrained optimization problems using;

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Explanation Constrained Optimization Eco

In a constrained optimization problem, the decisionmaker wants to select the optimal choice - the one most valuable to him or her - that;

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Accelerated Optimization for Machine Learning

This book on optimization includes forewords by Michael I. Jordan, Zongben Xu and Zhi-Quan Luo. Machine learning relies heavily on;

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Accelerated Optimization for Machine Learning

This book on optimization includes forewords by Michael I. Jordan, Zongben Xu and Zhi-Quan Luo. Machine learning relies heavily on;

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Large Scale PDE Constrained Optimization in Applications

applications involve some kind of optimization, it has been natural to extend the use of CFD tools from ?ow simulation to simu- tion based optimization;

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Inverse Radiosurgery Treatment Planning Through Deconvolution and Constrained Optimization

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Numerical Optimization

This book starts with illustrations of the ubiquitous character of optimization, and describes numerical algorithms in a tutorial way. It;

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Convex Optimization

This book provides easy access to the basic principles and methods for solving constrained and unconstrained convex optimization problems;

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Evolutionary Multi-Criterion Optimization

papers are divided into the following topical sections: theory; algorithms; dynamic multi-objective optimization; constrained multi-objective;

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Applied Optimization

of equations, non-linear systems of equations, unconstrained optimization, equality-constrained optimization and inequality-constrained optimization;

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Applied Optimization

of equations, non-linear systems of equations, unconstrained optimization, equality-constrained optimization and inequality-constrained optimization;

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Global Optimization

This self-contained monograph presents a new stochastic approach to global optimization problems arising in a variety of disciplines;

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Nonlinear Optimization in Electrical Engineering with Applications in MATLAB (R)

and adapt. Topics covered include: classical optimization methods one dimensional optimization unconstrained and constrained optimization;

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Numerical Optimization

, concentrating on methods for both unconstrained and constrained optimization.;

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Numerical Optimization

, concentrating on methods for both unconstrained and constrained optimization.;

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A Brief Introduction to Continuous Evolutionary Optimization

. Heuristic extensions are presented that allow optimization in constrained, multimodal and multi-objective solution spaces. An adaptive penalty;

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Portfolio Optimization

quadratic programming, the author discusses a constrained portfolio optimization problem and uses an algorithm to determine the entire (constrained;

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Frontiers in Algorithmics

, approximation algorithms, combinatorial optimization, parameterized algorithms, and online algorithms.;

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An Introduction to Nonlinear Optimization Theory

with the case of differentiable data and the classical results on constrained optimization problems, and continuing with the topic of nonsmooth;

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Solving Optimization Problems with MATLAB (R)

first. Focuses are made on the solutions of various types of optimization problems, including unconstrained and constrained optimizations, mixed;

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Foundations of Mathematical Economics

and constrained optimization. Rather than simply offer a collection of problem-solving techniques, the book emphasizes the unifying;

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Nonlinear Optimization

, duality theory, and numerical methods for solving unconstrained and constrained optimization problems. It addresses not only classical material;

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