摘要
基于增广拉格朗日法提出了一种快速分解算法求解Dantzig-Selector模型.与经典的乘子交替方向法相比,新算法的每个子问题都具有更简单易行的迭代格式.通过测试两种不同类型的随机数据,相应的数值计算结果表明,算法在CPU运行时间方面有较明显的优势.
Based on the augmented Lagrangian method, this paper introduces a fast decomposition algorithm for solving the Dantzig selector model. Comparing with the classical alternating direction method of multipliers, all subproblems of the proposed algorithm have closed-form solutions so that the new algorithm is easily implementable in practice. Finally some preliminary numerical results show that our new algorithm has superiority in terms of taking less CPU time by testing two types of synthetic data sets.
出处
《杭州电子科技大学学报（自然科学版）》
2016年第1期97-102,共6页
Journal of Hangzhou Dianzi University：Natural Sciences
基金
浙江省自然科学基金重点资助项目(LZ14A010003)
浙江省大学生新苗人才计划资助项目(2015R407038)
