<div class="csl-bib-body">
<div class="csl-entry">Filzmoser, P., Mayrhofer, M., Radojicic, U., & Lewitschnig, H. (2023). Explainable outlier identification for matrix-valued observations. In <i>Book of Abstracts : International Conference on Data Science : ICDS 2023 : Multidimensional Perspectives: From Statistical Learning to Data Science Applications</i> (pp. 13–13).</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/190530
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dc.description.sponsorship
European Commission
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dc.language.iso
en
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dc.subject
robust statistics
en
dc.subject
outlier detection
en
dc.subject
explainable AI
en
dc.title
Explainable outlier identification for matrix-valued observations
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.contributor.affiliation
Infineon Technologies Austria AG, Austria
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dc.description.startpage
13
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dc.description.endpage
13
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dc.relation.grantno
101007326-2 - AI4CSM
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dc.type.category
Abstract Book Contribution
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tuw.booktitle
Book of Abstracts : International Conference on Data Science : ICDS 2023 : Multidimensional Perspectives: From Statistical Learning to Data Science Applications