SIAM Journal on Discrete Mathematics, Volume 34, Issue 1, Page 825-842, January 2020.
A cut $\varepsilon$-sparsifier of a weighted graph $G$ is a reweighted 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 [Approximating s-t minimum cuts in O͂($n^2$) time, in Proceedings of the Twenty-Eighth Annual ACM Symposium on the Theory of Computing (STOC'96), 1996, pp. 47--55], cut sparsifiers have proved extremely influential and found various applications. Going beyond cut sparsifiers, Filtser and Krauthgamer [SIAM J. Discrete Math., 31 (2017), pp. 1263--1276] 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.

中文翻译：

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二进制CSP的稀疏化

SIAM离散数学杂志，第34卷，第1期，第825-842页，2020年1月。
加权图$ G $的削减$ \ varepsilon $分隔符是（G）线性大小的$ G $的重新加权子图，它保留所有削减的大小，直到$ \ varepsilon $的乘法因子。自Benczúr和Karger提出[在O͂（$ n ^ 2 $）时间中的最小最小削减，在《第二十八届ACM计算理论年度学术会议论文集》（STOC'96），1996年，第47- -55]，已证明切割稀疏器具有极大的影响力，并发现了各种应用。Filtser和Krauthgamer超越了削减稀疏器的概念[SIAM J.Discrete Math。，31（2017），第1263--1276页]对哪些二进制布尔CSP可以稀疏进行了精确分类。在本文中，我们将其结果扩展到任意有限域上的二进制CSP。