更快(而且仍然相当简单)的网络(非)可靠性无偏估计器

2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS) Pub Date : 2017-10-01 DOI:10.1109/FOCS.2017.75

David R Karger

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引用次数: 6

摘要

考虑当边以概率p失败时估计n顶点图的(非)可靠性的问题。我们表明，最小切的递归收缩算法，本质上不变，在n2+o(1)时间内运行，无论何时pc，都会产生恒定相对方差的无偏估计(因此具有相同时间界限的FPRAS)

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Faster (and Still Pretty Simple) Unbiased Estimators for Network (Un)reliability

Consider the problem of estimating the (un)reliability of an n-vertex graph when edges fail with probability p. We show that the Recursive Contraction Algorithms for minimum cuts, essentially unchanged and running in n2+o(1) time, yields an unbiased estimator of constant relative variance (and thus an FPRAS with the same time bound) whenever pc

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2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS)

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