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Browsing Кафедра інформатики та прикладної математики by Subject "machine learning"

Browsing Кафедра інформатики та прикладної математики by Subject "machine learning"

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  • Actuality of the problem of parametric identification of a mathematical model 
    Куропятник, Данило Іванович (Arnold E. Kiv, Serhiy O. Semerikov, Vladimir N. Soloviev, Andrii M. Striuk, 2018-12-27)
    The purpose of the article is to study the possibilities of increasing the efficiency of a mathematical model by identifying the parameters of an object. A key factor for parametrization can be called the consideration of ...
  • Adaptive Testing Model as the Method of Quality Knowledge Control Individualizing 
    Shapovalova, Nonna; Rybalchenko, Olena; Dotsenko, Iryna; Bilashenko, Svitlana; Striuk, Andrii; Levan, Saitgareev (Vadim Ermolayev, Frédéric Mallet, Vitaliy Yakovyna, Vyacheslav Kharchenko, Vitaliy Kobets, Artur Korniłowicz, Hennadiy Kravtsov, Mykola Nikitchenko, Serhiy Semerikov, Aleksander Spivakovsky, 2019-06-30)
    The mission of the work is to develop and theorize the efficiency of application of the knowledge control system on the basis of adaptive testing technology, which combines the specifics of the professional and educational ...
  • Advances in machine learning for the innovation economy: in the shadow of war 
    Danylchuk, Hanna B.; Семеріков, Сергій Олексійович; Данильчук, Ганна Борисівна (2023-08-28)
    This preface introduces the selected and revised papers presented at the 10th International Conference on Monitoring, Modeling & Management of Emergent Economy (M3E2 2022), held online in Ukraine, on November 17-18, 2022. ...
  • Comparisons of performance between quantum-enhanced and classical machine learning algorithms on the IBM Quantum Experience 
    Zahorodko, P. V.; Семеріков, Сергій Олексійович; Соловйов, Володимир Миколайович; Striuk, A. M.; Striuk, M. I.; Shalatska, H. M. (IOP Publishing, 2021-03-19)
    Machine learning is now widely used almost everywhere, primarily for forecasting. In the broadest sense, the machine learning objective may be summarized as an approximation problem, and the issues solved by various training ...
  • Convolutional neural networks for image classification 
    Tarasenko, Andrii O.; Yakimov, Yuriy V.; Соловйов, Володимир Миколайович (Arnold E. Kiv, Serhiy O. Semerikov, Vladimir N. Soloviev, Andrii M. Striuk, 2020-02-09)
    This paper shows the theoretical basis for the creation of convolutional neural networks for image classification and their application in practice. To achieve the goal, the main types of neural networks were considered, ...
  • Credit scoring model for microfinance organizations 
    Yaroshchuk, Svitlana O.; Shapovalova, Nonna N.; Striuk, Andrii M.; Rybalchenko, Olena H.; Dotsenko, Iryna O.; Bilashenko, Svitlana V. (Arnold E. Kiv, Serhiy O. Semerikov, Vladimir N. Soloviev, Andrii M. Striuk, 2020-02-09)
    The purpose of the work is the development and application of models for scoring assessment of microfinance institution borrowers. This model allows to increase the efficiency of work in the field of credit. The object ...
  • Experimental Economics and Machine Learning for Prediction of Emergent Economy Dynamics 
    Ків, Арнольд Юхимович; Семеріков, Сергій Олексійович; Соловйов, Володимир Миколайович; Kibalnyk, Liubov; Danylchuk, Hanna; Matviychuk, Andriy (Arnold Kiv, Serhiy Semerikov, Vladimir Soloviev, Liubov Kibalnyk, Hanna Danylchuk, Andriy Matviychuk, 2019-08-01)
    This is an introductory text to a collection of selected papers from the M3E2 2019: The 8th International Conference on Monitoring, Modeling & Management of Emergent Economy, which was held in Odessa, Ukraine, on the May ...
  • Forecasting of Cryptocurrency Prices Using Machine Learning 
    Derbentsev, Vasily; Matviychuk, Andriy; Соловйов, Володимир Миколайович (Springer, 2020-07-30)
    Our study is devoted to the problems of the short-term forecasting cryptocurrency time series using machine learning (ML) approach. Focus on studying of the financial time series allows to analyze the methodological ...
  • Machine learning of emerging markets in pandemic times 
    Ків, Арнольд Юхимович; Hryhoruk, Pavlo; Khvostina, Inesa; Solovieva, Victoria; Соловйов, Володимир Миколайович; Семеріков, Сергій Олексійович (Arnold Kiv, 2020-10-26)
    This is an introductory text to a collection of selected papers from the M3E2 2020 Summer: The Special Edition of International Conference on Monitoring, Modeling & Management of Emergent Economy, which was held in ...
  • Machine learning: technologies and potential application at mining companies 
    Зелінська, Сніжана Олександрівна (EDP Sciences, 2020-04-22)
    Implementation of machine learning systems is currently one of the most sought-after spheres of human activities at the interface of information technologies, mathematical analysis and statistics. Machine learning technologies ...
  • Quantum enhanced machine learning: An overview 
    Zahorodko, Pavlo V.; Modlo, Yevhenii O.; Kalinichenko, Olga O.; Selivanova, Tetiana V.; Семеріков, Сергій Олексійович; Загородько, Павло Володимирович; Модло, Євгеній Олександрович; Калініченко, Ольга Олександрівна; Селіванова, Тетяна Валеріївна (CEUR Workshop Proceedings, 2021-03-23)
    Machine learning is now widely used almost everywhere, primarily for forecasting. The main idea of the work is to identify the possibility of achieving a quantum advantage when solving machine learning problems on a ...

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