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Subcubic Equivalences between Path, Matrix and Triangle Problems

机译:路径,矩阵和三角形问题之间的子电平等效

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We say an algorithm on n by n matrices with entries in [-M, M] (or n-node graphs with edge weights from [-M, M]) is truly sub cubic if it runs in O(n^{3-delta} poly(log M)) time for some delta > 0. We define a notion of sub cubic reducibility, and show that many important problems on graphs and matrices solvable in O(n^3) time are equivalent under sub cubic reductions. Namely, the following weighted problems either all have truly sub cubic algorithms, or none of them do: - The all-pairs shortest paths problem (APSP). - Detecting if a weighted graph has a triangle of negative total edge weight. - Listing up to n^{2.99} negative triangles in an edge-weighted graph. - Finding a minimum weight cycle in a graph of non-negative edge weights. - The replacement paths problem in an edge-weighted digraph. - Finding the second shortest simple path between two nodes in an edge-weighted digraph. - Checking whether a given matrix defines a metric. - Verifying the correctness of a matrix product over the (min, +)-semiring. Therefore, if APSP cannot be solved in n^{3-eps} time for any eps > 0, then many other problems also need essentially cubic time. In fact we show generic equivalences between matrix products over a large class of algebraic structures used in optimization, verifying a matrix product over the same structure, and corresponding triangle detection problems over the structure. These equivalences simplify prior work on sub cubic algorithms for all-pairs path problems, since it now suffices to give appropriate sub cubic triangle detection algorithms. Other consequences of our work are new combinatorial approaches to Boolean matrix multiplication over the (OR, AND)-semiring (abbreviated as BMM). We show that practical advances in triangle detection would imply practical BMM algorithms, among other results. Building on our techniques, we give two new BMM algorithms: a derandomization of the recent combinatorial BMM algorithm of Bansal and Williams (- - FOCS'09), and an improved quantum algorithm for BMM.
机译:我们在n矩阵上说n矩阵中的n矩阵,如果它在o(n ^ {3-)中运行,则在[-m,m]的边缘权重的n节点图中的n节点图中的n矩阵是真实的子立方。 Delta} Poly(log m))某些三角形> 0的时间时间。我们定义了子立方体还原性的概念,并表明在O(n ^ 3)时间中可解析的图形和矩阵上的许多重要问题是等同于子立方缩减。即,以下加权问题都具有真正的Sub Cubic算法,或者它们都不是: - 全对最短路径问题(APSP)。 - 检测加权图是否具有负总边缘重量的三角形。 - 在边缘加权图中列出N ^ {2.99}负三角形。 - 在非负边缘重量的图表中找到最小权重周期。 - 边缘加权数字中的替换路径问题。 - 在边缘加权数字中找到两个节点之间的第二个最短简单路径。 - 检查给定矩阵是否定义了度量标准。 - 验证矩阵产品的正确性(min,+) - femiring。因此,如果APSP不能在任何EPS> 0中的N ^ {3-EPS}时间中解决,那么许多其他问题也需要基本上立方点。事实上,我们在优化中使用的大类代数结构上显示矩阵产品之间的通用等效,验证相同结构上的矩阵产物,以及结构上的相应三角形检测问题。这些等效命令简化了对全对路径问题的子立方算法的先前工作,因为它现在足以给出适当的子立方三角形检测算法。我们作品的其他后果是对Boolean矩阵乘法的新组合方法(或者,and)-semiring(缩写为bmm)。我们表明三角形检测中的实际进步将意味着实用的BMM算法,以及其他结果。在我们的技术上,我们提供了两个新的BMM算法:最近的BMM和WILIAMS( - FOCS'09)的组合BMM算法的嘲弄,以及用于BMM的改进量子算法。

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