An Efficient Sieving-Based Secant Method for Sparse Optimization Problems with Least-Squares Constraints

IF 2.6 1区数学 Q1 MATHEMATICS, APPLIED

SIAM Journal on Optimization Pub Date : 2024-06-13 DOI:10.1137/23m1594443

Qian Li, Defeng Sun, Yancheng Yuan

引用次数: 1

查看原文本刊更多论文

基于筛分的 Secant 高效方法，适用于具有最小二乘约束的稀疏优化问题

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

SIAM Journal on Optimization 数学-应用数学

CiteScore

5.30

自引率

9.70%

发文量

101

审稿时长

6-12 weeks

期刊介绍： The SIAM Journal on Optimization contains research articles on the theory and practice of optimization. The areas addressed include linear and quadratic programming, convex programming, nonlinear programming, complementarity problems, stochastic optimization, combinatorial optimization, integer programming, and convex, nonsmooth and variational analysis. Contributions may emphasize optimization theory, algorithms, software, computational practice, applications, or the links between these subjects.