正规化(语言学)
数学优化
惩罚法
数学
基数(数据建模)
秩(图论)
约束(计算机辅助设计)
最优化问题
应用数学
计算机科学
人工智能
组合数学
几何学
数据挖掘
作者
Zhaosong Lu,Xiaorui Li,Shuhuang Xiang
标识
DOI:10.1080/10556788.2022.2142583
摘要
In this paper, we consider a class of constrained optimization problems whose constraints involve a cardinality or rank constraint. The penalty formulation based on a partial regularization has recently been promoted in the literature to approximate these problems, which usually outperforms the penalty formulation based on a full regularization in terms of solution quality. Nevertheless, the relation between the penalty formulation with a partial regularizer and the original problem was not much studied yet. Under some suitable assumptions, we show that the penalty formulation based on a partial regularization is an exact reformulation of the original problem in the sense that they both share the same global minimizers. We also show that a local minimizer of the original problem is that of the penalty reformulation. These results provide some theoretical justification for the often-observed superior performance of the penalty model based on a partial regularizer over a corresponding full regularizer.
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