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Handbook of Semidefinite Programming

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Cover of 'Handbook of Semidefinite Programming'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Convex Analysis on Symmetric Matrices
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    Chapter 3 The Geometry of Semidefinite Programming
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    Chapter 4 Duality and Optimality Conditions
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    Chapter 5 Self-Dual Embeddings
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    Chapter 6 Robustness
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    Chapter 7 Error Analysis
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    Chapter 8 Symmetric Cones, Potential Reduction Methods and Word-by-Word Extensions
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    Chapter 9 Potential Reduction and Primal-Dual Methods
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    Chapter 10 Path-Following Methods
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    Chapter 11 Bundle Methods to Minimize the Maximum Eigenvalue Function
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    Chapter 12 Combinatorial Optimization
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    Chapter 13 Semidefinite Programming Relaxations of Nonconvex Quadratic Optimization
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    Chapter 14 Semidefinite Programming in Systems and Control Theory
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    Chapter 15 Structural Design
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    Chapter 16 Moment Problems and Semidefinite Optimization
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    Chapter 17 Design of Experiments in Statistics
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    Chapter 18 Matrix Completion Problems
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    Chapter 19 Eigenvalue Problems and Nonconvex Minimization
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    Chapter 20 Sequential, Quadratic Constrained, Quadratic Programming for General Nonlinear Programming
Attention for Chapter 11: Bundle Methods to Minimize the Maximum Eigenvalue Function
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