Matches in SemOpenAlex for { <https://semopenalex.org/work/W2974580947> ?p ?o ?g. }
- W2974580947 endingPage "1779" @default.
- W2974580947 startingPage "1744" @default.
- W2974580947 abstract "Previous chapter Next chapter Full AccessProceedings Proceedings of the 2022 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA)Deterministic algorithms for the Lovász Local Lemma: simpler, more general, and more parallelDavid G. HarrisDavid G. Harrispp.1744 - 1779Chapter DOI:https://doi.org/10.1137/1.9781611977073.71PDFBibTexSections ToolsAdd to favoritesExport CitationTrack CitationsEmail SectionsAboutAbstract The Lovász Local Lemma (LLL) is a keystone principle in probability theory, guaranteeing the existence of configurations which avoid a collection ℬ of “bad” events which are mostly independent and have low probability. In its simplest “symmetric” form, it asserts that whenever a bad-event has probability p and affects at most d bad-events, and epd < 1, then a configuration avoiding all ℬ exists. A seminal algorithm of Moser & Tardos (2010) (which we call the MT algorithm) gives nearly-automatic randomized algorithms for most constructions based on the LLL. However, deterministic algorithms have lagged behind. We address three specific shortcomings of the prior deterministic algorithms. First, our algorithm applies to the LLL criterion of Shearer (1985); this is more powerful than alternate LLL criteria and also removes a number of nuisance parameters and leads to cleaner and more legible bounds. Second, we provide parallel algorithms with much greater flexibility in the functional form of the bad-events. Third, we provide a derandomized version of the MT-distribution, that is, the distribution of the variables at the termination of the MT algorithm. We show applications to non-repetitive vertex coloring, independent transversals, strong coloring, and other problems. These give deterministic algorithms which essentially match the best previous randomized sequential and parallel algorithms. Previous chapter Next chapter RelatedDetails Published:2022eISBN:978-1-61197-707-3 https://doi.org/10.1137/1.9781611977073Book Series Name:ProceedingsBook Code:PRDA22Book Pages:xvii + 3771" @default.
- W2974580947 created "2019-09-26" @default.
- W2974580947 creator A5056288926 @default.
- W2974580947 date "2022-01-01" @default.
- W2974580947 modified "2023-10-18" @default.
- W2974580947 title "Deterministic algorithms for the Lovász Local Lemma: simpler, more general, and more parallel" @default.
- W2974580947 cites W1515157528 @default.
- W2974580947 cites W1976549152 @default.
- W2974580947 cites W1983085249 @default.
- W2974580947 cites W2008097118 @default.
- W2974580947 cites W2042125214 @default.
- W2974580947 cites W2047290604 @default.
- W2974580947 cites W2066969286 @default.
- W2974580947 cites W2067487847 @default.
- W2974580947 cites W2072075682 @default.
- W2974580947 cites W2072870176 @default.
- W2974580947 cites W2082905402 @default.
- W2974580947 cites W2087518343 @default.
- W2974580947 cites W2093066443 @default.
- W2974580947 cites W2096875564 @default.
- W2974580947 cites W2100061495 @default.
- W2974580947 cites W2109693504 @default.
- W2974580947 cites W2126274204 @default.
- W2974580947 cites W2156584294 @default.
- W2974580947 cites W2198255326 @default.
- W2974580947 cites W2395370258 @default.
- W2974580947 cites W2611754984 @default.
- W2974580947 cites W2623186112 @default.
- W2974580947 cites W2889036126 @default.
- W2974580947 cites W2949574609 @default.
- W2974580947 cites W2963080349 @default.
- W2974580947 cites W2963236013 @default.
- W2974580947 cites W2964046371 @default.
- W2974580947 cites W2964244155 @default.
- W2974580947 cites W2969466987 @default.
- W2974580947 cites W3010637297 @default.
- W2974580947 cites W3099612169 @default.
- W2974580947 cites W3117062007 @default.
- W2974580947 cites W3198979447 @default.
- W2974580947 doi "https://doi.org/10.1137/1.9781611977073.71" @default.
- W2974580947 hasPublicationYear "2022" @default.
- W2974580947 type Work @default.
- W2974580947 sameAs 2974580947 @default.
- W2974580947 citedByCount "4" @default.
- W2974580947 countsByYear W29745809472020 @default.
- W2974580947 countsByYear W29745809472021 @default.
- W2974580947 crossrefType "book-chapter" @default.
- W2974580947 hasAuthorship W2974580947A5056288926 @default.
- W2974580947 hasBestOaLocation W29745809472 @default.
- W2974580947 hasConcept C105795698 @default.
- W2974580947 hasConcept C11413529 @default.
- W2974580947 hasConcept C118615104 @default.
- W2974580947 hasConcept C121332964 @default.
- W2974580947 hasConcept C128669082 @default.
- W2974580947 hasConcept C132525143 @default.
- W2974580947 hasConcept C13533509 @default.
- W2974580947 hasConcept C149441793 @default.
- W2974580947 hasConcept C18903297 @default.
- W2974580947 hasConcept C2777759810 @default.
- W2974580947 hasConcept C2779662365 @default.
- W2974580947 hasConcept C33923547 @default.
- W2974580947 hasConcept C41008148 @default.
- W2974580947 hasConcept C46757340 @default.
- W2974580947 hasConcept C62520636 @default.
- W2974580947 hasConcept C80899671 @default.
- W2974580947 hasConcept C86803240 @default.
- W2974580947 hasConceptScore W2974580947C105795698 @default.
- W2974580947 hasConceptScore W2974580947C11413529 @default.
- W2974580947 hasConceptScore W2974580947C118615104 @default.
- W2974580947 hasConceptScore W2974580947C121332964 @default.
- W2974580947 hasConceptScore W2974580947C128669082 @default.
- W2974580947 hasConceptScore W2974580947C132525143 @default.
- W2974580947 hasConceptScore W2974580947C13533509 @default.
- W2974580947 hasConceptScore W2974580947C149441793 @default.
- W2974580947 hasConceptScore W2974580947C18903297 @default.
- W2974580947 hasConceptScore W2974580947C2777759810 @default.
- W2974580947 hasConceptScore W2974580947C2779662365 @default.
- W2974580947 hasConceptScore W2974580947C33923547 @default.
- W2974580947 hasConceptScore W2974580947C41008148 @default.
- W2974580947 hasConceptScore W2974580947C46757340 @default.
- W2974580947 hasConceptScore W2974580947C62520636 @default.
- W2974580947 hasConceptScore W2974580947C80899671 @default.
- W2974580947 hasConceptScore W2974580947C86803240 @default.
- W2974580947 hasLocation W29745809471 @default.
- W2974580947 hasLocation W29745809472 @default.
- W2974580947 hasOpenAccess W2974580947 @default.
- W2974580947 hasPrimaryLocation W29745809471 @default.
- W2974580947 hasRelatedWork W1480883248 @default.
- W2974580947 hasRelatedWork W1516091070 @default.
- W2974580947 hasRelatedWork W2065826935 @default.
- W2974580947 hasRelatedWork W2112526268 @default.
- W2974580947 hasRelatedWork W2172406734 @default.
- W2974580947 hasRelatedWork W2884603497 @default.
- W2974580947 hasRelatedWork W2922566013 @default.
- W2974580947 hasRelatedWork W3184929353 @default.
- W2974580947 hasRelatedWork W4307416302 @default.
- W2974580947 hasRelatedWork W4313227037 @default.
- W2974580947 isParatext "false" @default.