Coordinate and Subspace Optimization Methods for Linear Least Squares with Non-Quadratic Regularization

@inproceedings{Elad2006CoordinateAS,
title={Coordinate and Subspace Optimization Methods for Linear Least Squares with Non-Quadratic Regularization},
author={Michael Elad and Boaz Matalon and Michael Zibulevsky},
year={2006}
}

This work addresses the problem of regularized linear least squares (RLS) with non-quadratic separable regularization. Despite being frequently deployed in many applications, the RLS problem is often hard to solve using standard iterative methods. In a recent work [10], a new iterative method called Parallel Coordinate Descent (PCD) was devised. We provide herein a convergence analysis of the PCD algorithm, and also introduce a form of the regularization function, which permits analytical… CONTINUE READING