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首页> 外文会议>International Conference on Computational Science and Its Applications - ICCSA 2003 Pt.3 May 18-21, 2003 Montreal, Canada >Improved Monte Carlo Linear Solvers Through Non-diagonal Splitting
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Improved Monte Carlo Linear Solvers Through Non-diagonal Splitting

机译：通过非对角分裂改进的蒙特卡洛线性求解器

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摘要

Fast, but approximate, solutions to linear algebra problems have many potential applications, such as in graph partitioning, preconditioning, information retrieval, etc. Monte Carlo techniques appear attractive for such needs. While Monte Carlo linear solvers have a long history, their application has been limited due to slow convergence. Despite the development of techniques to improve their accuracy, current methods suffer from the drawback that they are stochastic realizations of inherently poor iterative methods. The reason for such choices is the need for efficient Monte Carlo implementation, which has restricted the splittings that are considered. However, in this paper we demonstrate that such restrictions are not necessarily required, and that efficient Monte Carlo implementations are possible even with splittings that do not appear amenable to it.
机译：线性代数问题的快速但近似的解决方案具有许多潜在的应用，例如在图分区，预处理，信息检索等方面。蒙特卡洛技术似乎对此类需求具有吸引力。尽管蒙特卡洛线性求解器历史悠久，但由于收敛速度慢，其应用受到限制。尽管开发了提高其准确性的技术，但是当前方法遭受的缺点是，它们是本质上较差的迭代方法的随机实现。做出此类选择的原因是需要高效的蒙特卡洛实现，这限制了所考虑的分歧。但是，在本文中，我们证明了这种限制不是必需的，并且即使使用看起来不适合它的拆分，有效的蒙特卡洛实现也是可能的。

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