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

IF 2.6 1区 数学 Q1 MATHEMATICS, APPLIED
Qian Li, Defeng Sun, Yancheng Yuan
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引用次数: 1

摘要

本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Efficient Sieving-Based Secant Method for Sparse Optimization Problems with Least-Squares Constraints
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来源期刊
SIAM Journal on Optimization
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.
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