/optLBFGS

Matlab code for the Limited-memory BFGS (Broyden–Fletcher–Goldfarb–Shanno) algorithm

Primary LanguageMATLABMIT LicenseMIT

optLBFGS

Matlab code for the Limited-memory BFGS (Broyden–Fletcher–Goldfarb–Shanno) algorithm.

  1. Limited-memory BFGS (L-BFGS) is an optimization algorithm in the family of quasi-Newton methods that approximates the Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm using a limited amount of computer memory. It is a popular algorithm for parameter estimation in machine learning. http://en.wikipedia.org/wiki/Limited-memory_BFGS

  2. I use line search algorithm satisfying strong Wolfe conditions. More details can be found from Algorithms 3.2 on page 59 in Numerical Optimization, by Nocedal and Wright http://sentientdesigns.net/math/mathbooks/Number%20theory/Numerical%20Optimization%20-%20J.%20Nocedal,%20S.%20Wright.pdf

  3. In example.m, Both optLBFGS and minFunc are used in solving 2 optimization problems(myfun and rosenbrock, the 2D Rosenbrock "banana" function). I believe optLBFGS has similar performance with minFunc( with limited-memory BFGS - default) in most of the cases.

Author: Guipeng Li

Email: guipenglee(AT)gmail.com