Notes for Numerical Optimization (2nd)

About

This is the notes for Numerical Optimization (2nd). Contributions are welcomed and you can submit a pull request on GitHub.

Contributors

• Mofii

Contents

• 3 Line Search Methods
  • 3.1 Introduction
  • 3.2 Convergence of Line Search Methods
  • 3.3 Rate of Convergence
  • 3.4 Newton’s Method with Hessian Modification
  • 3.5 Step-Length Selection Algorithms
• 4 Trust-Region Methods
  • 4.1 Algorithms Based on the Cauchy Point
  • 4.2 Global Convergence
• 5 Conjugate Gradient Methods
  • 5.1 The Linear Conjugate Gradient Method
  • 5.2 Nonlinear Conjugate Gradient Method
• 6 Quasi-Newton Methods
  • 6.1 The BFGS Method
  • 6.2 The SR1 Method
  • 6.3 The Broyden Class
  • 6.4 Convergence Analysis
• 7 Large-Scale Unconstrained Optimization
  • 7.1 Inexact Newton Methods
  • 7.4 Algorithms for Partially Separable Functions
• 8 Calculating Derivatives
  • 8.1 Finite-Difference Derivative Approximations