gauss_seidel_stochastic

gauss_seidel_stochastic, an Octave code which uses a stochastic version of the Gauss-Seidel iteration to solve a linear system with a symmetric positive definite (SPD) matrix.

The main interest of this code is that it is an understandable analogue to the stochastic gradient descent method used for optimization in various machine learning applications.

Licensing:

The computer code and data files described and made available on this web page are distributed under the MIT license

Languages:

gauss_seidel_stochastic is available in a MATLAB version and an Octave version and a Python version.

Related Data and Programs:

gauss_seidel_stochastic_test

test_matrix, a MATLAB code which defines test matrices.

Reference:

• Tim Kelley,
  Iterative Methods for Linear and Nonlinear Equations,
  SIAM, 2004,
  ISBN: 0898713528,
  LC: QA297.8.K45.

Source Code:

• gauss_seidel_stochastic.m, carries out multiple iterations of the stochastic Gauss-Seidel procedure.