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Knowledge injection via ML-based initialization of neural networks
Hoffmann, Lars
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Bartelt, Christian
;
Stuckenschmidt, Heiner
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Additional URL:
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http://ceur-ws.org/Vol-3052/
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URN:
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urn:nbn:de:0074-3052-0
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Document Type:
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Conference or workshop publication
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Year of publication:
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2021
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Book title:
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Proceedings of the CIKM 2021 Workshops (CIKMW 2021) co-located with 30th ACM International Conference on Information and Knowledge Management (CIKM 2021) : Gold Coast, Queensland, Australia, November 1-5,2021
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The title of a journal, publication series:
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CEUR Workshop Proceedings
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Volume:
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3052
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Page range:
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1-6
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Conference title:
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KINN 2021, 1st Workshop on Knowledge Injection in Neural Networks (KINN)
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Location of the conference venue:
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Online
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Date of the conference:
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01.11.2021
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Publisher:
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Cong, Gao
;
Ramanath, Maya
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Place of publication:
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Aachen, Germany
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Publishing house:
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RWTH Aachen
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ISSN:
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1613-0073
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Publication language:
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English
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Institution:
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Außerfakultäre Einrichtungen > Institut für Enterprise Systems (InES)
School of Business Informatics and Mathematics > Praktische Informatik II (Stuckenschmidt 2009-)
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Pre-existing license:
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 Creative Commons Attribution 4.0 International (CC BY 4.0)
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Subject:
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004 Computer science, internet
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Keywords (English):
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knowledge injection , neural networks , initialization , machine learning
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Abstract:
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Despite the success of artificial neural networks (ANNs) for various complex tasks, their performance and training duration heavily rely on several factors. In many application domains these requirements, such as high data volume and quality, are not satisfied. To tackle this issue, different ways to inject existing domain knowledge into the ANN generation provided promising results. However, the initialization of ANNs is mostly overlooked in this paradigm and remains an important scientific challenge. In this paper, we present a machine learning framework enabling an ANN to perform a semantic mapping from a well-defined, symbolic representation of domain knowledge to weights and biases of an ANN in a specified architecture.
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Additional information:
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KINN 2021, 1st Workshop on Knowledge Injection in Neural Networks (KINN) fand am 1.11.2011 im Rahmen der CIKM 2021 statt -- Online-Ressource
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 | Dieser Eintrag ist Teil der Universitätsbibliographie. |
 | Das Dokument wird vom Publikationsserver der Universitätsbibliothek Mannheim bereitgestellt. |
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