论文标题
随机kaczmarz平均
Randomized Kaczmarz with Averaging
论文作者
论文摘要
随机Kaczmarz（RK）方法是一种迭代方法，用于近似大型方程线性系统的最小二乘解决方案。标准RK方法使用顺序更新，使并行计算变得困难。在这里，我们研究了RK的并行版本，其中使用了独立更新的加权平均值。我们通过平均分析RK的收敛性，并通过经验证明其性能。我们表明，随着螺纹数量的增加，收敛速率会提高，而不一致的系统的收敛范围也会减少。
The randomized Kaczmarz (RK) method is an iterative method for approximating the least-squares solution of large linear systems of equations. The standard RK method uses sequential updates, making parallel computation difficult. Here, we study a parallel version of RK where a weighted average of independent updates is used. We analyze the convergence of RK with averaging and demonstrate its performance empirically. We show that as the number of threads increases, the rate of convergence improves and the convergence horizon for inconsistent systems decreases.
