Methods for L_p-L_q Minimization in Image Restoration and Regression - SIAM-IS Seminar

Explore methods for $\ell_p$-$\ell_q$ minimization and their applications in image restoration and regression with nonconvex loss and penalty in this one-hour virtual seminar. Delve into minimization problems with objective functions combining fidelity and regularization terms determined by p-norms and q-norms, respectively, where 0

Introduction
Overview
Problem
lasso method
norms
nonnegative pixels
Outline
Starting Point
Smooth Function
Adaptive Measurement
Convergence
Example
Crossvalidation
Sparse Representation
Tensor Products
Modulus iterative method
Relative error
Applications
Questions