Quantum enhanced machine learning: An overview

Please use this identifier to cite or link to this item: http://ds.knu.edu.ua/jspui/handle/123456789/3383

Title:	Quantum enhanced machine learning: An overview
Authors:	Zahorodko, Pavlo V. Modlo, Yevhenii O. Kalinichenko, Olga O. Selivanova, Tetiana V. Semerikov, Serhii Семеріков, Сергій Олексійович Семериков, Сергей Алексеевич
Keywords:	machine learning quantum computing quantum software engineering
Issue Date:	2021
Publisher:	CEUR Workshop Proceedings
Citation:	Quantum enhanced machine learning: An overview [Electronic resource] / Pavlo V. Zahorodko, Yevhenii O. Modlo, Olga O. Kalinichenko, Tetiana V. Selivanova, Serhiy O. Semerikov // Proceedings of the 3rd Workshop for Young Scientists in Computer Science & Software Engineering (CS&SE@SW 2020), Kryvyi Rih, Ukraine, November 27, 2020 / Edited by : Arnold E. Kiv, Serhiy O. Semerikov, Vladimir N. Soloviev, Andrii M. Striuk // CEUR Workshop Proceedings. – 2021. – Vol. 2832. – P. 94-103. – Access mode : http://ceur-ws.org/Vol-2832/paper13.pdf
Abstract:	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 quantum computer.
URI:	http://ceur-ws.org/Vol-2832/paper13.pdf http://ds.knu.edu.ua/jspui/handle/123456789/3383
ISSN:	1613-0073
Appears in Collections:	Кафедра професійної та соціально-гуманітарної освіти

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