All-Pairs LCA in DAGs: Breaking through the O(n2:5) barrier

被引:0
|
作者
Grandoni, Fabrizio [1 ]
Italiano, Giuseppe F. [2 ]
Lukasiewicz, Aleksander [3 ]
Parotsidis, Nikos [4 ]
Uznanskil, Przemyslaw [3 ]
机构
[1] IDSIA, Lugano, Switzerland
[2] LUISS Univ, Rome, Italy
[3] Univ Wroclaw, Wroclaw, Poland
[4] Google Res, Zurich, Switzerland
关键词
LOWEST COMMON ANCESTORS; ALGORITHMS; SEQUENCE;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Let G = (V,E) be an n-vertex directed acyclic graph (DAG). A lowest common ancestor (LCA) of two vertices u and v is a common ancestor w of u and v such that no descendant of w has the same property. In this paper, we consider the problem of computing an LCA, if any, for all pairs of vertices in a DAG. The fastest known algorithms for this problem exploit fast matrix multiplication subroutines and have running times ranging from O(n(2.687)) [Bender et al. SODA'01] down to O(n(2.615)) [Kowaluk and Lingas ICALP'05] and O(n(2.569)) [Czumaj et al. TCS'07]. Somewhat surprisingly, all those bounds would still be Omega(n(2.5)) even if matrix multiplication could be solved optimally (i.e., w = 2). This appears to be an inherent barrier for all the currently known approaches, which raises the natural question on whether one could break through the O(n(2.5)) barrier for this problem. In this paper, we answer this question affirmatively: in particular, we present an (O) over tilde (n(2.447)) ((O) over tilde (n(7/3)) for w = 2) algorithm for finding an LCA for all pairs of vertices in a DAG, which represents the first improvement on the running times for this problem in the last 13 years. A key tool in our approach is a fast algorithm to partition the vertex set of the transitive closure of G into a collection of O(l) chains and O(n/l) antichains, for a given parameter. As usual, a chain is a path while an antichain is an independent set. We then find, for all pairs of vertices, a candidate LCA among the chain and antichain vertices, separately. The first set is obtained via a reduction to (max; min) matrix multiplication. The computation of the second set can be reduced to Boolean matrix multiplication similarly to previous results on this problem. We finally combine the two solutions together in a careful (non-obvious) manner.
引用
收藏
页码:273 / 289
页数:17
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