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Conjugate Gradient Algorithms in Nonconvex Optimization

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Cover of 'Conjugate Gradient Algorithms in Nonconvex Optimization'

Table of Contents

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    Book Overview
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    Chapter 1 Conjugate Direction Methods for Quadratic Problems
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    Chapter 2 Conjugate Gradient Methods for Nonconvex Problems
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    Chapter 3 Memoryless Quasi-Newton Methods
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    Chapter 4 Preconditioned Conjugate Gradient Algorithms
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    Chapter 5 Limited Memory Quasi-Newton Algorithms
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    Chapter 6 The Method of Shortest Residuals and Nondifferentiable Optimization
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    Chapter 7 The Method of Shortest Residuals for Differentiable Problems
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    Chapter 8 The Preconditioned Shortest Residuals Algorithm
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    Chapter 9 Optimization on a Polyhedron
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    Chapter 10 Conjugate Gradient Algorithms for Problems with Box Constraints
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    Chapter 11 Preconditioned Conjugate Gradient Algorithms for Problems with Box Constraints
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    Chapter 12 Preconditioned Conjugate Gradient Based Reduced-Hessian Methods
Attention for Chapter 11: Preconditioned Conjugate Gradient Algorithms for Problems with Box Constraints
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