CholeskyQR is a simple and fast QR decomposition via Cholesky decomposition, while it has been considered highly sensitive to the condition number. In this paper, we provide a randomized preconditioner framework for CholeskyQR algorithm. Under this framework, two methods (randomized LU-CholeskyQR and randomized QR-CholeskyQR) are proposed and discussed. We prove the proposed preconditioners can effectively reduce the condition number, which is also demonstrated by numerical tests. Abundant numerical tests indicate our methods are more stable and faster than all the existing algorithms and have good scalability.
翻译:ChaleskyQR 是一个简单而快速的 QR 分解过程, 通过 Clolesky 分解方式进行快速的 QR 分解, 虽然它被认为对条件编号非常敏感 。 在本文中, 我们为 ChaleskyQR 算法提供了一个随机化的前提框架 。 在此框架下, 提出和讨论两种方法( 随机化 LU- CholeskyQR 和随机化 QR- CholeskyQR ) 。 我们证明, 提议的前提条件可以有效地减少条件编号, 并且通过数字测试来证明这一点 。 大量的数字测试表明, 我们的方法比所有现有的算法更稳定, 更快, 并且具有良好的可缩放性 。