Computing a Sparse Projection into a Box
Optimization and Control
2022-04-13 v1 Data Structures and Algorithms
Abstract
We describe a procedure to compute a projection of into the intersection of the so-called \emph{zero-norm} ball of radius , i.e., the set of -sparse vectors, with a box centered at a point of . The need for such projection arises in the context of certain trust-region methods for nonsmooth regularized optimization. Although the set into which we wish to project is nonconvex, we show that a solution may be found in operations. We describe our Julia implementation and illustrate our procedure in the context of two trust-region methods for nonsmooth regularized optimization.
Cite
@article{arxiv.2204.05429,
title = {Computing a Sparse Projection into a Box},
author = {Dominique Orban},
journal= {arXiv preprint arXiv:2204.05429},
year = {2022}
}
Comments
12 pages, 5 figures