二进制CSP的稀疏化
Sparsification of Binary CSPs
摘要：
加权图$G$的割$\varepsilon$ -稀疏子是$G$的一个重加权子图，它具有（准）线性大小，保持所有割的大小直到$\varepsilon$的一个乘法因子。自从Benczúr和Karger [STOC'96]引入以来，切割稀疏器已经证明是非常有影响力的，并找到了各种应用。超越削减稀疏，Filtser和Krauthgamer [SIDMA'17]给出了一个精确的分类，其中二进制布尔CSP是稀疏的。在本文中，我们将他们的结果推广到任意有限域上的二元CSP。
英文摘要：
A cut $\varepsilon$-sparsifier of a weighted graph $G$ is a re-weighted subgraph of $G$ of (quasi)linear size that preserves the size of all cuts up to a multiplicative factor of $\varepsilon$. Since their introduction by Benczúr and Karger [STOC'96], cut sparsifiers have proved extremely influential and found various applications. Going beyond cut sparsifiers, Filtser and Krauthgamer [SIDMA'17] gave a precise classification of which binary Boolean CSPs are sparsifiable. In this paper, we extend their result to binary CSPs on arbitrary finite domains.
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。
