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
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