Approximating Maximum Matching Requires Almost Quadratic Time
Soheil Behnezhad, Mohammad Roghani, Aviad Rubinstein
摘要
We study algorithms for estimating the size of maximum matching. This problem has been subject to extensive research. For n-vertex graphs, Bhattacharya, Kiss, and Saranurak [FOCS'23] (BKS) showed that an estimate that is within εn of the optimal solution can be achieved in n 2-Ωε(1) time, where n is the number of vertices. While this is subquadratic in n for any fixed ε > 0, it gets closer and closer to the trivial Θ(n 2 ) time algorithm that reads the entire input as ε is made smaller and smaller.
In this work, we close this gap and show that the algorithm of BKS is close to optimal. In particular, we prove that for any fixed δ > 0, there is another fixed ε = ε(δ) > 0 such that estimating the size of maximum matching within an additive error of εn requires Ω(n 2-δ ) time in the adjacency list model.
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引用它的顶会 Paper7
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它引用的顶会 Paper10
- Space Efficient Approximation to Maximum Matching Size from Uniform Edge SamplesMichael Kapralov, Slobodan Mitrovic, Ashkan Norouzi-Fard, Jakab TardosSODA 2020 · 被引用 30 次
- Time-Optimal Sublinear Algorithms for Matching and Vertex CoverSoheil BehnezhadFOCS 2021 · 被引用 16 次
- Dynamic Algorithms for Maximum Matching SizeSoheil BehnezhadSODA 2023 · 被引用 14 次
- Dynamic Matching with Better-than-2 Approximation in Polylogarithmic Update TimeSayan Bhattacharya, Peter Kiss, Thatchaphol Saranurak, David WajcSODA 2023 · 被引用 11 次
- Dynamic (1+ϵ)-Approximate Matching Size in Truly Sublinear Update TimeSayan Bhattacharya, Peter Kiss, Thatchaphol SaranurakFOCS 2023 · 被引用 9 次
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