Lifted Marginal Filtering for Asymmetric Models by Clustering-Based Merging.

Stefan Lüdtke; Marcel Gehrke; Tanya Braun; Ralf Möller; Thomas Kirste

doi:10.3233/FAIA200397

Lifted Marginal Filtering for Asymmetric Models by Clustering-Based Merging.

Stefan Lüdtke, Marcel Gehrke, Tanya Braun, Ralf Möller, Thomas Kirste

Originalsprache	Englisch
Titel	ECAI
Seitenumfang	8
Erscheinungsdatum	2020
Seiten	2608-2615
DOIs	https://doi.org/10.3233/FAIA200397
Publikationsstatus	Veröffentlicht - 2020

UN SDGs

Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung

SDG 3 – Gesundheit und Wohlergehen
SDG 4 – Qualitativ hochwertige Bildung
SDG 9 – Industrie, Innovation und Infrastruktur
SDG 11 – Nachhaltige Städte und Gemeinschaften
SDG 12 – Verantwortungsvoller Konsum und Produktion
SDG 14 – Lebensraum Wasser
SDG 15 – Lebensraum Land

Strategische Forschungsbereiche und Zentren

Zentren: Zentrum für Künstliche Intelligenz Lübeck (ZKIL)
Querschnittsbereich: Intelligente Systeme

Dokumente

10.3233/FAIA200397

Zitieren

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title = "Lifted Marginal Filtering for Asymmetric Models by Clustering-Based Merging.",

author = "Stefan L{\"u}dtke and Marcel Gehrke and Tanya Braun and Ralf M{\"o}ller and Thomas Kirste",

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AU - Kirste, Thomas

N1 - DBLP License: DBLP's bibliographic metadata records provided through http://dblp.org/ are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.

PY - 2020

Y1 - 2020

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DO - 10.3233/FAIA200397

M3 - Conference contribution

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