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https://ceur-ws.org/Vol-2917/preface.pdf
Vasyl Lytvyn
Michael Emmerich
Victoriа Vysotska
Vitor Basto-Fernandes
Volodymyr Lytvynenko
(Eds.)
Modern Machine Learning
Technologies and Data Science
Workshop
Workshop Proceedings of the 10th International Conference on
“Mathematics. Information Technologies. Education”, MoMLeT&DS
Workshop 2021
Lviv-Shatsk, Ukraine
June, 2021
Emmerich, M., Lytvyn, V., Vysotska, V., Basto-Fernandes, V., Lytvynenko, V. (Eds.): Modern Ma-
chine Learning Technologies and Data Science Workshop. Proc. 3rd International Workshop MoM-
LeT&DS 2021. Lviv-Shatsk, Ukraine, June 5-6, 2021, CEUR-WS.org, online
This volume represents the proceedings of the Workshop of the 10th International Conference on
“Mathematics. Information Technologies. Education”, with Posters and Demonstrations track, of the
3rd International Workshop of Modern Machine Learning Technologies and Data Science, held in
Lviv-Shatsk, Ukraine, in June 2021. It comprises 48 contributed papers that were carefully peer-
reviewed and selected from 63 submissions. The volume opens with the abstracts of the keynote talks.
The rest of the collection is organized in two parts. Parts I contain the contributions to the Main
MoMLeT&DS Workshop tracks, structured in one topical section: Modern Machine Learning Tech-
nologies and Data Science.
Copyright © 2021 for the individual papers by the papers’ authors. Copying permitted
only for private and academic purposes. This volume is published and copyrighted by
its editors.
Preface
It is our pleasure to present you the proceedings of the MoMLeT&DS Workhop of the 10th Inter-
national Conference on “Mathematics. Information Technologies. Education”, the first edition of the
Modern Machine Learning Technologies and Data Science Workshop, held in Lviv-Shatsk (Ukraine)
on June 5-6, 2021.
The main purpose of the MoMLeT&DS Workhop is to provide a forum for researchers to discuss
models for machine learning, multicriteria decision analysis and multiobjective optimization, and their
real-life applications. In MoMLeT&DS 2021, is encourage the submission of papers on machine
learning, decision making, multiobjective optimization and multicriteria decision analysis areas. Nov-
el applications of these methods to real world problems are welcome.
The conference is soliciting literature review, survey and research papers comments including,
whilst not limited to, the following areas of interest:
Regression analysis; Multiobjective Optimization;
Deep learning; Group Decision Making;
Gradient Boosted Trees; Multiattribute Utility or Value Theory;
Support Vector Machines; Behavioral Issues in Decision Making;
Bayesian networks; Preference Modelling;
Unsupervised learning for clustering; Applications of MCDM and
MCDM Theory; Optimization.
The language of MoMLeT&DS Workshop is English. The conference took the form of oral
presentation by invited keynote speakers plus presentations of peer-reviewed individual papers. There
was also an exhibition area for poster and demo sessions. A Student section of the conference for stu-
dents and PhD students runs in parallel to the main conference. The conference took the form of oral
presentation by invited keynote speakers plus presentations of peer-reviewed individual papers. The
papers were distributed among 47 external reviewers from France, The Netherlands, United King-
dom, Poland, Indonesia, India, Germany, Czech Republic, Portugal, Kingdom of Saudi Arabia and
Ukraine. The total number of reviews is 145. To take more correct decision regarding the acceptance
or rejection the papers got 2-5 reviews. The conference gathered participants from different countries
including India, Kazakhstan, Morocco, Ukraine and Netherlands.
This year the Organizing Committee received 63 submissions, out of which 48 were accepted for
presentation as regular papers. The papers are submitted to the following tracks: Regression analysis
(3 papers); Deep learning (5 papers); Gradient Boosted Trees (6 papers); Support Vector Machines
(3 papers); Bayesian networks (3 papers); Unsupervised learning for clustering (3 papers); MCDM
Theory (9 papers); Multiobjective Optimization (6 papers); Group Decision Making (7 papers); Mul-
tiattribute Utility or Value Theory (5 papers); Behavioral Issues in Decision Making (6 papers); Pref-
erence Modelling (3 papers); Applications of MCDM and Optimization (15 papers).
These papers and extended abstracts were published in this Volume of MoMLeT&DS Workshop
2021 proceedings. The conference would not have been possible without the support of many people.
First of all, we would like to thank all the authors who submitted papers to MoMLeT&DS 2021 and
thus demonstrated their interest in the research problems within our scope. We are very grateful to the
members of our Program Committee for providing timely and thorough reviews and, also, for being
cooperative in doing additional review work. We would like to thank the Organizing Committee of
the conference whose devotion and efficiency made this instance of MoMLeT&DS a very interesting
and effective scientific forum.
June, 2021 Vasyl Lytvyn
Michael Emmerich
Victoriа Vysotska
Vitor Basto-Fernandes
Volodymyr Lytvynenko