基于正交化的贪婪双子空间坐标下降法
Greedy double subspaces coordinate descent method via orthogonalization
摘要:
坐标下降法是求解大型线性最小二乘问题的一种有效的迭代法。在本文中,对于高度相干列的情况下,我们构造了一个有效的坐标下降法迭代投影的估计到一个解决方案的空间,通过Gram-Schmidt正交化的两个greenly选定的超平面形成。我们的方法可以被看作是一个简单的块版本的坐标下降法,其中涉及两个活动列。文中给出了该方法的收敛性分析,并通过数值模拟证实了该方法对具有高度相干列的矩阵的有效性。
英文摘要:
The coordinate descent method is an effective iterative method for solving large linear least-squares problems. In this paper, for the highly coherent columns case, we construct an effective coordinate descent method which iteratively projects the estimate onto a solution space formed by two greedily selected hyperplanes via Gram-Schmidt orthogonalization. Our methods may be regarded as a simple block version of coordinate descent method which involves two active columns. The convergence analysis of this method is provided and numerical simulations also confirm the effectiveness for matrices with highly coherent columns.
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