Regularization
Covers matrix based ordinary least squares regression, discretization of Fredholm and Voltarra integral equations, and matrix-based regularization approaches to solve ill-posed problems.
⏻ Learning Objectives
By the end of this module you have learned
how to apply matrix based ordinary regression to find multi-linear regression parameters to fit data.
how to discretize integral equations to cast them into matrix form.
how to analyze matrices to determine the degree to which problems are ill posed.
how to apply regularization to invert ill-posed matrix equations.
how to apply common approaches to identify the optimal regularization parameter.
Slides and Lecture Notes
Notes: NotesNotebooks
Notebook: Regression, Inversion, and RegularizationHomework
⌨ Assignments
CC BY-NC 4.0 Markus Petters.