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Algorithmic Improvements of the Lovász Local Lemma via Cluster Expansion

机译:通过集群扩展对Lovász局部引理的算法改进

摘要

The Lovasz Local Lemma (LLL) is a powerful tool that can be used to prove that an object having none of a set of bad properties exists, using the probabilistic method. In many applications of the LLL it is also desirable to explicitly construct the combinatorial object. Recently it was shown that this is possible using a randomized algorithm in the full asymmetric LLL setting [R. Moser and G. Tardos, 2010]. A strengthening of the LLL for the case of dense local neighborhoods proved in [R. Bissacot et al., 2010] was recently also made constructive in [W. Pegden, 2011]. In another recent work [B. Haupler, B. Saha, A. Srinivasan, 2010], it was proved that the algorithm of Moser and Tardos is still efficient even when the number of events is exponential. Here we prove that these last two contributions can be combined to yield a new version of the LLL.
机译:Lovasz局部引理(LLL)是一种功能强大的工具,可以使用概率方法来证明没有一组不良特性的对象存在。在LLL的许多应用中,还希望显式构造组合对象。最近显示,在完全不对称的LLL设置中使用随机算法是可行的。 Moser和G. Tardos,2010年]。在[R. Bissacot等,2010]最近在[W.佩格登,2011年]。在最近的另一篇著作中[B. Haupler,B. Saha,A. Srinivasan,2010],事实证明,即使事件数是指数级的,Moser和Tardos的算法仍然有效。在这里,我们证明可以将这两个最后的贡献结合起来以产生LLL的新版本。

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