arXivDaily arXiv每日学术速递 周一至周五更新
arXiv周末暂无论文更新,休息一下吧,周末愉快~~
arXiv 2203.00671cs.DS
收藏

几乎线性时间的最大流与最小费用流

Maximum Flow and Minimum-Cost Flow in Almost-Linear Time

Li Chen, Rasmus Kyng, Yang P. Liu, Richard Peng, Maximilian Probst Gutenberg, Sushant Sachdeva

摘要:

我们给出了一个算法,计算精确的最大流和最小成本流的有向图与$m$边缘和多项式有界的整体需求,成本和容量在$m^{1+o(1)}$时间。我们的算法通过一系列的$m^{1+o(1)}$近似无向最小比率周期,其中每个周期的计算和处理摊销$m^{o(1)}$时间使用一个新的动态图数据结构的流。我们的框架扩展到运行在$m^{1+o(1)}$时间的算法计算流,最大限度地减少一般的边缘可分离凸函数的高精度。这给出了几个问题的几乎线性时间算法,包括熵正则化的最优运输,矩阵缩放,$p$ -范数流,和$p$ -范数保序回归任意有向无环图。

英文摘要:

We give an algorithm that computes exact maximum flows and minimum-cost flows on directed graphs with $m$ edges and polynomially bounded integral demands, costs, and capacities in $m^{1+o(1)}$ time. Our algorithm builds the flow through a sequence of $m^{1+o(1)}$ approximate undirected minimum-ratio cycles, each of which is computed and processed in amortized $m^{o(1)}$ time using a new dynamic graph data structure. Our framework extends to algorithms running in $m^{1+o(1)}$ time for computing flows that minimize general edge-separable convex functions to high accuracy. This gives almost-linear time algorithms for several problems including entropy-regularized optimal transport, matrix scaling, $p$-norm flows, and $p$-norm isotonic regression on arbitrary directed acyclic graphs.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑