FASTEN:用于图形挖掘的快速Sylvester方程求解器FASTEN: Fast Sylvester Equation Solver for Graph Mining |
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课程网址: | http://videolectures.net/kdd2018_du_fasten_sylvester_equation/ |
主讲教师: | Boxin Du |
开课单位: | 亚利桑那州立大学 |
开课时间: | 2018-11-23 |
课程语种: | 英语 |
中文简介: | Sylvester方程为各种重要的图挖掘任务提供了一个强大而统一的基元,包括网络对齐、图核、节点相似性、子图匹配等。Sylvestr方程的一个主要瓶颈在于其高计算复杂度。尽管付出了巨大的努力,但最先进的方法仍然需要在图的节点数量上至少为二次方的复杂性,即使使用近似。在本文中,我们提出了一系列基于Krylov子空间的算法(FASTEN),以加快和扩大用于图挖掘的Sylvester方程的计算。所提出方法的关键思想是将原始等效线性系统投影到Kronecker Krylov子空间上。我们进一步利用(1)解矩阵的隐式表示以及相关的计算,以及(2)将原始西尔维斯特方程分解为一组较小尺寸的相互关联的西尔维斯特方程。所提出的算法具有两个显著的特点。首先,它们提供了没有任何近似误差的精确解。其次,它们显著降低了求解Sylvester方程的时间和空间复杂性,其中两种算法在时间和空间上都具有线性复杂性。在一组不同的真实网络上进行的实验评估表明,我们的方法(1)比共轭梯度方法快10000倍,共轭梯度方法是输出精确解的最著名的竞争对手,并且(2)可扩展到百万个节点图。 |
课程简介: | The Sylvester equation offers a powerful and unifying primitive for a variety of important graph mining tasks, including network alignment, graph kernel, node similarity, subgraph matching, etc. A major bottleneck of Sylvester equation lies in its high computational complexity. Despite tremendous effort, state-of-the-art methods still require a complexity that is at least quadratic in the number of nodes of graphs, even with approximations. In this paper, we propose a family of Krylov subspace based algorithms (FASTEN) to speed up and scale up the computation of Sylvester equation for graph mining. The key idea of the proposed methods is to project the original equivalent linear system onto a Kronecker Krylov subspace. We further exploit (1) the implicit representation of the solution matrix as well as the associated computation, and (2) the decomposition of the original Sylvester equation into a set of inter-correlated Sylvester equations of smaller size. The proposed algorithms bear two distinctive features. First, they provide the exact solutions without any approximation error. Second, they significantly reduce the time and space complexity for solving Sylvester equation, with two of the proposed algorithms having a linear complexity in both time and space. Experimental evaluations on a diverse set of real networks, demonstrate that our methods (1) are up to 10, 000× faster against Conjugate Gradient method, the best known competitor that outputs the exact solution, and (2) scale up to million-node graphs. |
关 键 词: | FASTEN; 图形挖掘; 快速Sylvester方程求解器; Kronecker Krylov子空间; Sylvester方程; 图挖掘任务 |
课程来源: | 视频讲座网 |
数据采集: | 2023-03-27:cyh |
最后编审: | 2023-05-19:liyy |
阅读次数: | 31 |