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  • 标题:Probabilistic Logarithmic-Space Algorithms for Laplacian Solvers
  • 本地全文:下载
  • 作者:Dean Doron ; Fran{\c{c}}ois Le Gall ; Amnon Ta-Shma
  • 期刊名称:LIPIcs : Leibniz International Proceedings in Informatics
  • 电子版ISSN:1868-8969
  • 出版年度:2017
  • 卷号:81
  • 页码:41:1-41:20
  • DOI:10.4230/LIPIcs.APPROX-RANDOM.2017.41
  • 出版社:Schloss Dagstuhl -- Leibniz-Zentrum fuer Informatik
  • 摘要:A recent series of breakthroughs initiated by Spielman and Teng culminated in the construction of nearly linear time Laplacian solvers, approximating the solution of a linear system Lx=b, where L is the normalized Laplacian of an undirected graph. In this paper we study the space complexity of the problem. Surprisingly we are able to show a probabilistic, logspace algorithm solving the problem. We further extend the algorithm to other families of graphs like Eulerian graphs (and directed regular graphs) and graphs that mix in polynomial time. Our approach is to pseudo-invert the Laplacian, by first "peeling-off" the problematic kernel of the operator, and then to approximate the inverse of the remaining part by using a Taylor series. We approximate the Taylor series using a previous work and the special structure of the problem. For directed graphs we exploit in the analysis the Jordan normal form and results from matrix functions.
  • 关键词:Laplacian solvers; Randomized logspace; Bounded-space complexity classes; Random walks; Matrix computation
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