4.0 Article

A Constructive Lovasz Local Lemma for Permutations

期刊

THEORY OF COMPUTING
卷 13, 期 -, 页码 -

出版社

UNIV CHICAGO, DEPT COMPUTER SCIENCE
DOI: 10.4086/toc.2017.v013a017

关键词

Lovasz Local Lemma; Lopsided Lovasz Local Lemma; random permutations; Moser-Tardos algorithm; Latin transversals; rainbow Hamiltonian cycles; strong chromatic number; hypergraph packing

资金

  1. NSF [CNS-1010789, CCF-1422569]
  2. Adobe, Inc.
  3. Division of Computing and Communication Foundations
  4. Direct For Computer & Info Scie & Enginr [1422569] Funding Source: National Science Foundation

向作者/读者索取更多资源

While there has been significant progress on algorithmic aspects of the Lovasz Local Lemma (LLL) in recent years, a noteworthy exception is when the LLL is used in the context of random permutations. The breakthrough algorithm of Moser & Tardos only works in the setting of independent variables, and does not apply in this context. We resolve this by developing a randomized polynomial-time algorithm for such applications. A noteworthy application is for Latin transversals: the best general result known here (Bissacot et al., improving on Erdos and Spencer), states that any n x n matrix in which each entry appears at most (27/256)n. times, has a Latin transversal. We present the first polynomial-time algorithm to construct such a transversal. We also develop RNC algorithms for Latin transversals, rainbow Hamiltonian cycles, strong chromatic number, and hypergraph packing. In addition to efficiently finding a configuration which avoids bad events, the algorithm of Moser & Tardos has many powerful extensions and properties. These include a well-characterized distribution on the output distribution, parallel algorithms, and a partial resampling variant. We show that our algorithm has nearly all of the same useful properties as the Moser-Tardos algorithm, and present a comparison of this aspect with recent work on the LLL in general probability spaces.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.0
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据