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https://ceur-ws.org/Vol-3312/preface.pdf
Michael Emmerich
Victoriа Vysotska
(Eds.)
Modern Machine Learning
Technologies and Data Science
Workshop
Workshop Proceedings of the 11th International Conference on
“Mathematics. Information Technologies. Education”, MoMLeT&DS
Workshop 2022
Leiden-Lviv, The Netherlands-Ukraine
November, 2022
Emmerich, M., Vysotska, V. (Eds.): Modern Machine Learning Technologies and Data Science
Workshop. Proc. 4th International Workshop MoMLeT&DS 2022. Leiden-Lviv, The Netherlands-
Ukraine, November 25-26, 2022, CEUR-WS.org, online
This volume represents the proceedings of the Workshop of the 11th International Conference on
“Mathematics. Information Technologies. Education”, with Posters and Demonstrations track, of the
4th International Workshop of Modern Machine Learning Technologies and Data Science, held in
Leiden-Lviv (The Netherlands-Ukraine), in November 2022. It comprises 28 contributed papers that
were carefully peer-reviewed and selected from 53 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 contribu-
tions to the Main MoMLeT&DS Workshop tracks, structured in one topical section: Modern Machine
Learning Technologies and Data Science.
Copyright © 2022 for the individual papers by the papers’ authors. Copying is permit-
ted 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 11th Inter-
national Conference on “Mathematics. Information Technologies. Education”, the 4th edition of the
Modern Machine Learning Technologies and Data Science Workshop, held in Leiden-Lviv (The
Netherlands-Ukraine) on November 25-26, 2022.
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 2022, 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 32 external reviewers from The Netherlands, Germany, France, United
Kingdom, China, Austria, Czech Republic, Portugal, India, Poland, Ukraine and Ukraine. The total
number of reviews is 162. To take more correct decision regarding the acceptance or rejection the
papers got 2-7 reviews. The conference gathered participants from different countries including The
Netherlands, Germany, United States, Poland, Estonia, Saudi Arabia, Turkey, Philippines, China,
India, Ukraine.
This year the Organizing Committee received 53 submissions, out of which 28 were accepted for
presentation as regular papers. The papers are submitted to the following tracks: Regression analysis
(6 papers); Deep learning (6 papers); Gradient Boosted Trees (3 papers); Support Vector Machines
(3 papers); Bayesian networks (3 papers); Unsupervised learning for clustering (3 papers); MCDM
Theory (3 papers); Multiobjective Optimization (1 papers); Group Decision Making (3 papers); Mul-
tiattribute Utility or Value Theory (1 papers); Behavioral Issues in Decision Making (3 papers); Pref-
erence Modelling (1 papers); Applications of MCDM and Optimization (3 papers).
These papers and extended abstracts were published in this Volume of MoMLeT&DS Workshop
2022 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 2022 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.
November, 2022 Michael Emmerich
Victoriа Vysotska