4.3 Article

Entropy compression versus Lovasz Local Lemma

期刊

ADVANCES IN APPLIED MATHEMATICS
卷 125, 期 -, 页码 -

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.aam.2021.102163

关键词

Probabilistic method in combinatorics; Lovasz Local Lemma; Randomized algorithms

资金

  1. Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq) [306853/2018-3, 310392/2017-9]
  2. Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES-PRINT) [88887.474425/2020-00]
  3. Fundacao de Amparo a Pesquisa do Estado de Minas Gerais (FAPEMIG) [PPM-00144-18, PPM 00600/16]

向作者/读者索取更多资源

In the context of the probabilistic method in combinatorics, a systematic exploration of the entropy compression method was conducted, clarifying its applicability and providing a general constructive criterion. Through specific examples, the effectiveness of the entropy-compression criterion was demonstrated in comparison with the Lovasz Local Lemma criterion and the improved criterion based on cluster expansion.
In the framework of the probabilistic method in combinatorics, we provide a systematization of the entropy compression method clarifying the setting in which it can be applied and providing a theorem yielding a general constructive criterion. We finally elucidate, through topical examples, the effectiveness of the entropy-compression criterion in comparison with the Lovasz Local Lemma criterion and, in particular, with the improved criterion based on cluster expansion. (C) 2021 Elsevier Inc. All rights reserved.

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