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arXiv 1610.02420cs.DScs.DMmath.CO
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Moser-Tardos框架中的偏倚依赖性:超越偏倚Lovász局部引理

Lopsidependency in the Moser-Tardos framework: Beyond the Lopsided Lovasz Local Lemma

David G. Harris

AI总结:

本文为Moser-Tardos算法提出一个强于偏倚Lovász局部引理的新收敛判据,改进k-SAT可满足性界,并引入新的并行算法,覆盖顺序算法适用的大多数场景。

摘要:

偏倚Lovász局部引理(LLLL)是一个强大的概率原理,已被用于各种组合构造中。虽然最初是关于概率空间的一般性陈述,但最近已被转化为多种多项式时间算法。Moser和Tardos(2010)的重采样算法是其中最著名的例子。针对LLLL,已有多种判据被证明;最强可能的判据由Shearer给出,而其他在计算上更易使用的判据由Bissacot等人(2011)、Pegden(2014)、Kolipaka和Szegedy(2011)以及Kolipaka、Szegedy和Xu(2012)提出。我们为Moser-Tardos算法的收敛性展示了一个新判据。该判据强于LLLL判据;这之所以可能,是因为它不像原始LLLL那样适用于相同的普遍性;然而,它足够强大,能够覆盖LLLL在组合学中的许多应用。我们展示了各种新的界和算法。一个值得注意的应用是针对具有有界变量出现次数的$k$-SAT问题。如Gebauer、Szábo和Tardos(2011)所示,每个变量出现次数$L \leq \frac{2^{k+1}}{e (k+1)}$的$k$-SAT实例是可满足的。尽管这个界在$k$方面是渐近紧的,我们将其改进为$L \leq \frac{2^{k+1} (1 - 1/k)^k}{k-1} - \frac{2}{k}$,当$k$较小时这可能显著更强。我们为LLLL引入了一种新的并行算法。虽然Moser和Tardos描述了Lovász局部引理的一个简单并行算法,并描述了偏倚引理的一种形式的简单顺序算法,但他们未能将两者结合。我们的新算法几乎适用于顺序算法可行的所有设置——这包括由我们新的更强LLLL判据所覆盖的设置。

英文摘要:

The Lopsided Lovász Local Lemma (LLLL) is a powerful probabilistic principle which has been used in a variety of combinatorial constructions. While originally a general statement about probability spaces, it has recently been transformed into a variety of polynomial-time algorithms. The resampling algorithm of Moser & Tardos (2010) is the most well-known example of this. A variety of criteria have been shown for the LLLL; the strongest possible criterion was shown by Shearer, and other criteria which are easier to use computationally have been shown by Bissacot et al (2011), Pegden (2014), Kolipaka & Szegedy (2011), and Kolipaka, Szegedy, Xu (2012). We show a new criterion for the Moser-Tardos algorithm to converge. This criterion is stronger than the LLLL criterion; this is possible because it does not apply in the same generality as the original LLLL; yet, it is strong enough to cover many applications of the LLLL in combinatorics. We show a variety of new bounds and algorithms. A noteworthy application is for $k$-SAT, with bounded occurrences of variables. As shown in Gebauer, Szábo, and Tardos (2011), a $k$-SAT instance in which every variable appears $L \leq \frac{2^{k+1}}{e (k+1)}$ times, is satisfiable. Although this bound is asymptotically tight (in $k$), we improve it to $L \leq \frac{2^{k+1} (1 - 1/k)^k}{k-1} - \frac{2}{k}$ which can be significantly stronger when $k$ is small. We introduce a new parallel algorithm for the LLLL. While Moser & Tardos described a simple parallel algorithm for the Lovász Local Lemma, and described a simple sequential algorithm for a form of the Lopsided Lemma, they were not able to combine the two. Our new algorithm applies in nearly all settings in which the sequential algorithm works --- this includes settings covered by our new stronger LLLL criterion.

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