Data Science and Reliable Machine Learning - 4th International Workshop - Revised Contributions

Aug 2, 2026

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Proceedings for the 4th International Workshop held at the American University of Armenia, featuring seventeen selected and carefully revised papers focused on Data Science and Reliable Machine Learning. The preface frames the workshop around the integration of artificial intelligence into smart environments driven by rapidly growing data from sensors, networks, services, and multimodal communication. It emphasizes requirements such as data quality, privacy and security, model interpretability, explainability, and practical deployment in industrial and mission-critical scenarios.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages170

Reading Time7 h 8 min

AccessFree to download

Preface

Workshop background and aims

Data quality, privacy, and security

Model interpretability and explainability

Aram Hajian, Nelson Baloian, Tomoo Inoue, Wolfram Luther (Eds.) Data Science and Reliable Machine Learning Logos Verlag Berlin λογος Bibliographic information published by Die Deutsche Bibliothek Die Deutsche Bibliothek lists this publication in the Deutsche Nationalbibliogra􀀌e; detailed bibliographic data is available in the Internet at [http://dnb.d-nb.de](http://dnb.d-nb.de). The Open Access publication of this title was made possible with the support from the Publication Fund of the University Library of Duisburg-Essen. The online edition of this work is also freely accessible via DuEPublico, the University Library Duisburg-Essen repository, and can be used under a Creative Commons License (CC BY-NC-SA 4.0, [https://creativecommons.org/licenses/by](https://creativecommons.org/licenses/by)nc-sa/4.0/) . This license allows reusers to distribute, remix, adapt, and build upon the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator. If you remix, adapt, or build upon the material, you must license the modi􀀌ed material under identical terms. Logos Verlag Berlin GmbH 2024 ISBN 978-3-8325-5855-0 DOI 10.30819/5855 Logos Verlag Berlin GmbH Georg-Knorr-Str. 4, Geb. 10, 12681 Berlin Tel.: +49 (0)30 / 42 85 10 90 Fax: +49 (0)30 / 42 85 10 92 [https://www.logos-verlag.com](https://www.logos-verlag.com) Aram Hajian, Nelson Baloian, Tomoo Inoue, Wolfram Luther (Eds.) Data Science and Reliable Machine Learning 4th International Workshop at the American University of Armenia, College of Science & Engineering October 3–6, 2024 Co-organized with IEEE Computer Society Armenia Chapter and Supported by the Foundation for Armenian Science and Technology Revised contributions Volume Editors Aram Hajian American University of Armenia, College of Science and Engineering 40 Marshal Baghramyan Ave, Yerevan 0019, Armenia Email: [ahajian@aua.am](ahajian@aua.am) Nelson Baloian Department of Computer Science, Universidad de Chile Blanco Encalada 2120, Santiago 6511224, Chile [E-mail: ](E-mail: nbaloian@dcc.uchile.cl)[nbaloian@dcc.uchile.cl](E-mail: nbaloian@dcc.uchile.cl) Tomoo Inoue University of Tsukuba, Faculty of Library, Information and Media Science 1-2, Kasuga, Tsukuba, Ibaraki, 305-8550, Japan E-mail: [inoue@slis.tsukuba.ac.jp](inoue@slis.tsukuba.ac.jp) Wolfram Luther University of Duisburg-Essen, Scientific Computing, Computer Graphics, and Image Processing Lotharstr. 65 (LF), 47057 Duisburg, Germany [E-mail: ](E-mail: wolfram.luther@uni-due.de)[wolfram.luther@uni-due.de](E-mail: wolfram.luther@uni-due.de) 2012 ACM CCS: Security and privacy ā Computer system organization ā Computing methodologies ā Applied computing ā Human-centered computing W PREFACE After three successful versions of the Workshop on Collaborative Technologies and Data Science in Smart City Applications (CODASSCA 2018, 2020, and 2022) we are glad to present proceedings of the fourth version held at the American University of Armenia (AUA), October 3–6, 2024 in Yerevan, Armenia. Data Science and Reliable Machine Learning (ML) presents seventeen selected and carefully revised papers, which are available at the start of the workshop in the Open Access Proceedings and as a printed version. Society, technologies, and sciences are undergoing a rapid and revolutionary shift towards the integration of artificial intelligence into every system that people use in everyday life to create smart environments (SmE) through ambient intelligence (AmI) in highly connected and collaborative scenarios. The main source and asset for making smart systems is data, produced today in extraordinary large quantities. Data volumes are growing rapidly due to environmental sensor reading, sensor networks, broadband services, multimodal communication, whereas pervasive and embedded computing is enhancing the capability of everyday objects and easing collaboration a

FAQs

What event do these proceedings cover?

They cover the 4th International Workshop at the American University of Armenia (AUA), held October 3–6, 2024 in Yerevan, Armenia.

How many papers are included in the proceedings?

The proceedings present seventeen selected and carefully revised papers.

What main challenges are highlighted for reliable machine learning?

The preface highlights data quality requirements and the need for privacy and security, along with the low interpretability and limited explainability of many ML models, especially for industrial and mission-critical use.

Aug 2, 2026

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