English

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 wRnw \in \mathbb{R}^n into the intersection of the so-called \emph{zero-norm} ball kB0k \mathbb{B}_0 of radius kk, i.e., the set of kk-sparse vectors, with a box centered at a point of kB0k \mathbb{B}_0. 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 O(nlog(n))O(n \log(n)) 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

R2 v1 2026-06-24T10:45:08.618Z