Implicit Directed Acyclic Graphs (DAGs) for Parallel Outlier/Anomaly Detection Ensembles

David Muhr, Michael Affenzeller, Josef Küng

Publikation: Beitrag in Buch/Bericht/TagungsbandKonferenzbeitragBegutachtung

Abstract

We present a methodology to automatically parallelize outlier detection ensemble models using directed acyclic graphs embedding the MapReduce paradigm. The DAGs are built implicitly such that naive sequential computations can be transformed into efficient parallel computations without changing the underlying implementation. We show that the proposed parallelization approach is an effective strategy to combat the computational complexity inherent to ensemble learning models, leading to a near-optimal speedup in a theoretical setting, and a substantial speedup in a practical setting.

OriginalspracheEnglisch
TitelArtificial Intelligence Applications and Innovations - 19th IFIP WG 12.5 International Conference, AIAI 2023, Proceedings
Redakteure/-innenIlias Maglogiannis, Lazaros Iliadis, John MacIntyre, Manuel Dominguez
Herausgeber (Verlag)Springer
Seiten3-15
Seitenumfang13
ISBN (Print)9783031341069
DOIs
PublikationsstatusVeröffentlicht - 2023
Veranstaltung19th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2023 - León, Spanien
Dauer: 14 Juni 202317 Juni 2023

Publikationsreihe

NameIFIP Advances in Information and Communication Technology
Band676 IFIP
ISSN (Print)1868-4238
ISSN (elektronisch)1868-422X

Konferenz

Konferenz19th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2023
Land/GebietSpanien
OrtLeón
Zeitraum14.06.202317.06.2023

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