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arXiv 2411.19366cs.DScs.DM
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加权$k$-拟阵交的更优近似算法

Better Approximation for Weighted $k$-Matroid Intersection

Neta Singer, Theophile Thiery

AI总结:

针对加权$k$-拟阵交及更通用的加权拟阵$k$-奇偶问题,提出基于随机归约迭代求解近无权重实例的方法,首次改进了长期存在的近似比保证。

摘要:

我们研究在公共基础集上,寻找同时属于$k$个拟阵的最大权独立集的问题。该$k$-拟阵交问题在诸多场景中自然出现,例如图与超图匹配问题的推广场景中。本文提出了一种针对加权$k$-拟阵交问题的$(k+1)/(2 \ln 2)$-近似算法,这是对Lee、Sviridenko和Vondrák(2009)提出的长期以来的$(k-1)$近似保证的首次改进。在此过程中,我们还针对更通用的加权拟阵$k$-奇偶问题,给出了首个优于贪心算法的结果。我们的核心创新在于一种随机归约方法:通过迭代求解几乎无权重的实例。该视角让我们能够借鉴无权重问题的研究思路——Lee、Sviridenko和Vondrák已为无权重问题设计了$k/2$-近似算法。我们通过构造精细化的拟阵交换、利用随机性规避不良局部极小值,对该过程进行了分析。

英文摘要:

We consider the problem of finding an independent set of maximum weight simultaneously contained in $k$ matroids over a common ground set. This $k$-matroid intersection problem appears naturally in many contexts, for example in generalizing graph and hypergraph matching problems. In this paper, we provide a $(k+1)/(2 \ln 2)$-approximation algorithm for the weighted $k$-matroid intersection problem. This is the first improvement over the longstanding $(k-1)$-guarantee of Lee, Sviridenko and Vondrák (2009). Along the way, we also give the first improvement over greedy for the more general weighted matroid $k$-parity problem. Our key innovation lies in a randomized reduction in which we solve almost unweighted instances iteratively. This perspective allows us to use insights from the unweighted problem for which Lee, Sviridenko, and Vondrák have designed a $k/2$-approximation algorithm. We analyze this procedure by constructing refined matroid exchanges and leveraging randomness to avoid bad local minima.

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。

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