Special Issue "Selected Papers from CD-MAKE 2021 and ARES 2021"

A special issue of Machine Learning and Knowledge Extraction (ISSN 2504-4990).

Deadline for manuscript submissions: 31 December 2021.

Special Issue Editors

Prof. Dr. Simon Tjoa
E-Mail Website
Guest Editor
Josef Ressel Centre for Blockchains and Security Management, St. Pölten University of Applied Sciences, 3100 St. Pölten, Austria
Interests: security management; cyber resilience; resilient AI; trustworthy AI
Special Issues and Collections in MDPI journals
Prof. Dr. Edgar Weippl
E-Mail Website
Guest Editor
SBA Research, University of Vienna, 1090 Vienna, Austria
Interests: fundamental and applied research on blockchain and distributed ledger technologies; security of production systems engineering
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Prof. Dr. Andreas Holzinger
E-Mail Website1 Website2
Guest Editor
Human-Centered AI Lab (Holzinger Group), Institute for Medical Informatics, Statistics and Documentation, Medical University Graz, 8036 Graz, Austria
Interests: artificial intelligence (AI); machine learning (ML); explainable AI (xAI); causability; decision support systems; medical AI; health informatics
Special Issues and Collections in MDPI journals
Peter Kieseberg
E-Mail Website1 Website2
Guest Editor Assistant
SBA Research GmbH, St. Pölten University of Applied Sciences, 1040 Vienna, Austria
Interests: digital forensics; privacy aware machine learning; trustworthy AI; blockchain and AI

Special Issue Information

Dear Colleagues,

This Special Issue will mainly consist of extended papers selected from papers presented at the 5th International Cross Domain Conference for Machine Learning & Knowledge Extraction (CD-MAKE 2021) as well as the 16th International Conference on Availability, Reliability and Security (ARES 2021). Please visit the conference websites for a detailed description: https://www.ares-conference.eu/ and https://cd-make.net/

Prof. Dr. Simon Tjoa
Prof. Dr. Edgar Weippl
Prof. Dr. Andreas Holzinger
Peter Kieseberg
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Machine Learning and Knowledge Extraction is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • DATA – data fusion, preprocessing, mapping, knowledge representation, environments, etc.
  • LEARNING – algorithms, contextual adaptation, causal reasoning, transfer learning, etc.
  • VISUALIZATION – intelligent interfaces, human-AI interaction, dialogue systems, explanation interfaces, etc.
  • PRIVACY – data protection, safety, security, reliability, verifiability, trust, ethics and social issues, etc.
  • NETWORK – graphical models, graph-based machine learning, Bayesian inference, etc.
  • TOPOLOGY – geometrical machine learning, topological and manifold learning, etc. ENTROPY – time and machine learning, entropy-based learning, etc.

Published Papers

This special issue is now open for submission.
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