Jingbang Chen, Mehrdad Ghadiri, Hoai-An Nguyen, Richard Peng, Junzhao Yang
{"title":"Entrywise Approximate Laplacian Solving","authors":"Jingbang Chen, Mehrdad Ghadiri, Hoai-An Nguyen, Richard Peng, Junzhao Yang","doi":"arxiv-2409.10022","DOIUrl":null,"url":null,"abstract":"We study the escape probability problem in random walks over graphs. Given\nvertices, $s,t,$ and $p$, the problem asks for the probability that a random\nwalk starting at $s$ will hit $t$ before hitting $p$. Such probabilities can be\nexponentially small even for unweighted undirected graphs with polynomial\nmixing time. Therefore current approaches, which are mostly based on\nfixed-point arithmetic, require $n$ bits of precision in the worst case. We\npresent algorithms and analyses for weighted directed graphs under\nfloating-point arithmetic and improve the previous best running times in terms\nof the number of bit operations. We believe our techniques and analysis could\nhave a broader impact on the computation of random walks on graphs both in\ntheory and in practice.","PeriodicalId":501525,"journal":{"name":"arXiv - CS - Data Structures and Algorithms","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Data Structures and Algorithms","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.10022","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
We study the escape probability problem in random walks over graphs. Given
vertices, $s,t,$ and $p$, the problem asks for the probability that a random
walk starting at $s$ will hit $t$ before hitting $p$. Such probabilities can be
exponentially small even for unweighted undirected graphs with polynomial
mixing time. Therefore current approaches, which are mostly based on
fixed-point arithmetic, require $n$ bits of precision in the worst case. We
present algorithms and analyses for weighted directed graphs under
floating-point arithmetic and improve the previous best running times in terms
of the number of bit operations. We believe our techniques and analysis could
have a broader impact on the computation of random walks on graphs both in
theory and in practice.
我们研究图上随机行走的逃逸概率问题。在给定了$s,t,$和$p$三个顶点的情况下,该问题要求计算从$s$开始的随机行走在到达$p$之前到达$t$的概率。即使是对于多项式混合时间的无权无向图,这种概率也可能是指数级小的。因此,目前的方法大多基于定点运算,在最坏的情况下需要 n 个比特的精度。我们提出了浮点运算下的加权有向图算法和分析,并在比特运算次数方面改进了之前的最佳运行时间。我们相信,我们的技术和分析会对图上随机游走的理论和实践计算产生更广泛的影响。