gauss_seidel_stochastic, a Python 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.
The information on this web page is distributed under the MIT license.
gauss_seidel_stochastic is available in a MATLAB version and an Octave version and a Python version.
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