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Probabilistic methods: entropy compression

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Authors : Kardoš, František (Author of the conference)
CIRM (Publisher )

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Abstract : We will overview two probabilistic methods used to prove the existence of diverse combinatorial objects with desired properties: First, we will introduce Lovász Local Lemma as a classical tool to prove that, informally speaking, with non-zero probability none of the “bad” events occur if those bad events are of low probability and somewhat essentially independent from each other. Next, we will move on to its algorithmic counterpart, the Entropy Compression Method, used to ensure that a randomized algorithm eventually finds a solution with desired properties. The two methods will be illustrated by applying them to various settings in graph theory, combinatorics, and geometry.
https://www.labri.fr/perso/fkardos/

Keywords : probabilistic method; Lovász Local Lemma; entropy compression method

MSC Codes :
05C15 - Coloring of graphs and hypergraphs
05C80 - Random graphs

Additional resources :
https://www.cirm-math.fr/RepOrga/3048/Slides/Kardos-I.pdf
https://www.cirm-math.fr/RepOrga/3048/Notes/Exos_kardos.pdf

    Information on the Video

    Film maker : Hennenfent, Guillaume
    Language : French
    Available date : 29/03/2024
    Conference Date : 11/03/2024
    Subseries : Research School
    arXiv category : Combinatorics ; Discrete Mathematics
    Mathematical Area(s) : Combinatorics
    Format : MP4 (.mp4) - HD
    Video Time : 01:10:29
    Targeted Audience : Researchers ; Graduate Students ; Doctoral Students, Post-Doctoral Students
    Download : https://videos.cirm-math.fr/2024-03-14_Kardoš.mp4

Information on the Event

Event Title : ALEA Days / Journées ALEA
Event Organizers : Clément, Julien ; Courtiel, Julien ; David, Julien ; Mishna, Marni
Dates : 11/03/2024 - 15/03/2024
Event Year : 2024
Event URL : https://conferences.cirm-math.fr/3048.html

Citation Data

DOI : 10.24350/CIRM.V.20151003
Cite this video as: Kardoš, František (2024). Probabilistic methods: entropy compression. CIRM. Audiovisual resource. doi:10.24350/CIRM.V.20151003
URI : http://dx.doi.org/10.24350/CIRM.V.20151003

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