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Optimization tutorial

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Optimization tutorial

by Mark Bangert

 

30 Jan 2012

Set of functions for convex optimization including different optimization and line search algorithms

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Description

This archive includes a set of functions introducing into optimization and line search techniques. It was designed for educational purposes.

Most of the functions run as script on toy problems. It is possible to visualize the line search and experiment with different update rules for the inverse Hessian in order to understand the optimization process.

This package includes

* conjugate gradient
* BFGS algorithm
* LBFGS algorithm
* Levenberg Marquart algorithm
* backtraicking Armijo line search
* line search enforcing strong Wolfe conditions
* line search bases on a 1D quadratic approximation of the objective function
* a function for naive numerical differentation

Have fun!

References:

* Nocedal & Wright: Numerical optimizaion

MATLAB release MATLAB 7.11 (2010b)
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Tag Applied By Date/Time
convex optimization Mark Bangert 30 Jan 2012 10:05:42
line search Mark Bangert 30 Jan 2012 10:05:42
lbfgs Mark Bangert 30 Jan 2012 10:05:42
bfgs Mark Bangert 30 Jan 2012 10:05:42
conjugate gradient Mark Bangert 30 Jan 2012 10:05:42
levenberg marquart Mark Bangert 30 Jan 2012 10:05:42
backtracking line search Mark Bangert 30 Jan 2012 10:05:42
armijo line search Mark Bangert 30 Jan 2012 10:05:42
strong wolfe conditions Mark Bangert 30 Jan 2012 10:05:42

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