Descent methods and line search: preconditioned steepest descent

Bierlaire (2015) Optimization: principles and algorithms, EPFL Press. Section 11.1

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Descent method and line search: quadratic interpolation
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Descent method and line search: quadratic interpolation

Descent methods and line search: first Wolfe condition
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Descent methods and line search: first Wolfe condition

Applied Optimization - Steepest Descent
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Applied Optimization - Steepest Descent

23. Accelerating Gradient Descent (Use Momentum)
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23. Accelerating Gradient Descent (Use Momentum)

Preconditioned Conjugate Gradient Descent (ILU)
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Preconditioned Conjugate Gradient Descent (ILU)

Gradient Descent, Step-by-Step
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Gradient Descent, Step-by-Step

Why the gradient is the direction of steepest ascent
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Why the gradient is the direction of steepest ascent

Descent methods with line search: Newton method with line search
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Descent methods with line search: Newton method with line search

Trust Regions
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Trust Regions

Line Search 1
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Line Search 1

8.1 Quasi Newton Methods Part I
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8.1 Quasi Newton Methods Part I

Descent methods and line search: inexact line search
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Descent methods and line search: inexact line search

Intro to Gradient Descent || Optimizing High-Dimensional Equations
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Intro to Gradient Descent || Optimizing High-Dimensional Equations

Lecture -- Steepest Ascent Method
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Lecture -- Steepest Ascent Method

8.2 Quasi Newton and BFGS
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8.2 Quasi Newton and BFGS

Search Direction 1
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Search Direction 1

Penalty Methods
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Penalty Methods

[CFD] Conjugate Gradient for CFD (Part 1): Background and Steepest Descent
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[CFD] Conjugate Gradient for CFD (Part 1): Background and Steepest Descent

Descent methods and line search: validity of the Wolfe conditions
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Descent methods and line search: validity of the Wolfe conditions