Fredman's Trick Meets Dominance Product: Fine-Grained Complexity of Unweighted APSP, 3SUM Counting, and More

PROCEEDINGS OF THE 55TH ANNUAL ACM SYMPOSIUM ON THEORY OF COMPUTING, STOC 2023(2023)

引用 2|浏览27
暂无评分
摘要
In this paper we carefully combine Fredman's trick [SICOMP'76] and Matousek's approach for dominance product [IPL'91] to obtain powerful results in fine-grained complexity. Under the hypothesis that APSP for undirected graphs with edge weights in {1, 2,..., n} requires n(3-o(1)) time (when omega = 2), we show a variety of conditional lower bounds, including an n(7/3-o(1)) lower bound for unweighted directed APSP and an n(2.2-o(1)) lower bound for computing the Minimum Witness Product between two n x n Boolean matrices, even if omega = 2, improving upon their trivial n(2) lower bounds. Our techniques can also be used to reduce the unweighted directed APSP problem to other problems. In particular, we show that (when omega = 2), if unweighted directed APSP requires n(2.5-o(1)) time, then Minimum Witness Product requires n(7/3-o(1)) time. We showthat, surprisingly, many central problems in fine-grained complexity are equivalent to their natural counting versions. In particular, we show that Min-Plus Product and Exact Triangle are subcubically equivalent to their counting versions, and 3SUM is subquadratically equivalent to its counting version. We also obtain new algorithms using new variants of the Balog-Szemeredi-Gowers theorem from additive combinatorics. For example, we get an O(n(3.83)) time deterministic algorithm for exactly counting the number of shortest paths in an arbitrary weighted graph, improving the textbook (O) over tilde (n(4)) time algorithm. We also get faster algorithms for 3SUM in preprocessed universes, and deterministic algorithms for 3SUM on monotone sets in {1, 2,..., n}(d)
更多
查看译文
关键词
fine-grained complexity
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要