An Ensemble Interpretable Machine Learning Scheme for Securing Data Quality at the Edge

Karanika, A., Oikonomou, P., Kolomvatsos, K. and Anagnostopoulos, C. (2020) An Ensemble Interpretable Machine Learning Scheme for Securing Data Quality at the Edge. In: CD-MAKE Cross Domain Conference for Machine Learning and Knowledge Extraction, All-Digital Conference, 25-28 Aug 2020, (Accepted for Publication)

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Abstract

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Item Type:Conference Proceedings
Additional Information:CD-MAKE is a joint effort of IFIP TC 5, IFIP TC 12, IFIP WG 8.4, IFIP WG 8.9 and IFIP WG 12.9 and is held as an all-digital conference in conjunction with the 15th International Conference on Availability, Reliability and Security ARES 2020.
Status:Accepted for Publication
Refereed:Yes
Glasgow Author(s) Enlighten ID:Anagnostopoulos, Dr Christos
Authors: Karanika, A., Oikonomou, P., Kolomvatsos, K., and Anagnostopoulos, C.
College/School:College of Science and Engineering > School of Computing Science
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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
301654Intelligent Applications over Large Scale Data StreamsChristos AnagnostopoulosEuropean Commission (EC)745829Computing Science