M. Emmerich); Preface: modern machine learning technologies workshop Michael Emmerich m.t.m.emmerich@liacs.leidenuniv.nl 0 1 2 4 Vasyl Lytvyn Vasyl.V.Lytvyn@lpnu.ua 3 4 Victoria Vysotska victoria.a.vysotska@lpnu.ua 3 4 5 Department of IT, University of Jyväskylä , Mattilanniemi 2, 40100 Jyväskylä , Finland Lead AI Scientist @ SILO.ai , Lapinlahdenkatu 1 C, 00180 Helsinki , Finland Leiden Institute of Advanced Computer Science, LIACS Leiden University , Niels Bohrweg 1, 2333CA Leiden , The Netherlands Lviv Polytechnic National University , Stepan Bandera 12, 79013 Lviv , Ukraine MoMLeT-2024: 6th International Workshop on Modern Machine Learning Technologies , May, 31 - June, 1, 2024, Lviv-Shatsk , Ukraine Osnabrück University , Friedrich-Janssen-Str. 1, 49076 Osnabrück , Germany 2090 000 0 0002

This document is the preface of the 6th International Workshop on Modern Machine Learning Technologies (MoMLeT-2024), May, 31 - June, 1, 2024, held in Lviv-Shatsk, Ukraine. The main purpose of the MoMLeT Workshop is providing a forum for researchers to discuss models for machine learning, multicriteria decision analysis and multi-objective optimization, and their real-life applications.

 machine learning deep learning model method theory tools technology system 1. Introduction

The main purpose of the Modern Machine Learning Technologies Workshop is providing a forum for researchers to discuss models for machine learning, multicriteria decision analysis and multi-objective optimization, and their real-life applications [ 1-5 ]. In MoMLeT Workshop, we encourage the submission of papers on deep learning, decision making, and multicriteria decision analysis areas. The MoMLeT Workshop is soliciting literature review, survey and research papers comments including, whilst not limited to, the following areas of interest:  

Regression analysis; Deep learning;

          

 Gradient Boosted Trees;

Support Vector Machines; Bayesian networks; Unsupervised learning for clustering; MCDM Theory; Multi-objective Optimization; Group Decision Making; Multi-attribute Utility or Value Theory; Behavioral Issues in Decision Making; Preference Modelling;

Applications of MCDM and Optimization.

The language of Modern Machine Learning Technologies Workshop is English.

The Modern Machine Learning Technologies Workshop took the form of oral presentation by peer-reviewed individual papers. The papers were distributed among 32 external reviewers from The Netherlands, Finland, Germany, France, United Kingdom, China, Austria, Czech Republic, Portugal, India, Poland, Ukraine and Ukraine.

The Modern Machine Learning Technologies Workshop gathered participants from different countries including Germany, USA, United Kingdom, The Netherlands, Finland, Poland, China, and Ukraine.

This year Organizing Committee received 39 submissions, out of which 21 were accepted for presentation as a regular paper. These papers and extended abstracts were published in this Volume I of the 6th International Workshop on Modern Machine Learning Technologies (MoMLeT 2024) proceedings.

 2. Acknowledgments

The Modern Machine Learning Technologies Workshop 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 Modern Machine Learning Technologies Workshop 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 workshop whose devotion and efficiency made this instance of Modern Machine Learning Technologies Workshop a very interesting and effective scientific forum. We would like to thank Modern Machine Learning Technologies Workshop Chairs, as well as Program Committee and all Reviewers, for their diligence in selecting the papers and ensuring their high scientific quality. URL: https://dblp.uni-trier.de/db/conf/momlet/momlet2023.html, https://ceurws.org/Vol-3426/. [2] M. Emmerich, V. Vysotska, Proceedings of the Modern Machine Learning Technologies and Data Science Workshop (MoMLeT&DS 2022), Leiden-Lviv, The Netherlands-Ukraine, November 25-26, 2022, CEUR Workshop Proceedings 3312, CEUR-WS.org 2023. URL: https://dblp.unitrier.de/db/conf/momlet/momlet2022.html, https://ceur-ws.org/Vol-3312/. [3] M. Emmerich, V. Lytvyn, V. Vysotska, V. Lytvynenko, V. Basto-Fernandes, Proceedings of the Modern Machine Learning Technologies and Data Science Workshop (MoMLeT&DS 2021), Lviv-Shatsk, Ukraine, June 5-6, 2021, CEUR Workshop Proceedings 2917, CEUR-WS.org 2021. URL: https://dblp.unitrier.de/db/conf/momlet/momlet2021.html, https://ceur-ws.org/Vol-2917/. [4] M. Emmerich, V. Lytvyn, V. Vysotska, V. Basto-Fernandes, V. Lytvynenko, Proceedings of the Modern Machine Learning Technologies and Data Science Workshop (MoMLeT&DS 2020), Lviv-Shatsk, Ukraine, June 2-3, 2020, CEUR Workshop Proceedings 2631, CEUR-WS.org 2020. URL: https://dblp.unitrier.de/db/conf/momlet/momlet2020.html, https://ceur-ws.org/Vol-2631/. [5] M. Emmerich, V. Lytvyn, I. Yevseyeva, V. Basto-Fernandes, D. Dosyn, V. BastoFernandes, V. Vysotska, Proceedings of the Modern Machine Learning Technologies and Data Science Workshop (MoMLeT&DS 2019), Lviv-Shatsk, Ukraine, June 2-4, 2019, CEUR Workshop Proceedings 2386, CEUR-WS.org 2019. URL: https://dblp.uni-trier.de/db/conf/momlet/momlet2019.html, https://ceurws.org/Vol-2386/.

 [1] M. Emmerich , V. Vysotska , V. Lytvynenko , Proceedings of the Modern Machine Learning Technologies and Data Science Workshop (MoMLeT&DS 2023 ), Lviv, Ukraine, June 3, 2023 , CEUR Workshop Proceedings 3426, CEUR-WS.org 2023 .