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http://elibrary.kdpu.edu.ua/xmlui/handle/123456789/4357| Назва: | Quantum enhanced machine learning: An overview |
| Автори: | 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 |
| Ключові слова: | machine learning quantum computing quantum software engineering |
| Дата публікації: | 23-бер-2021 |
| Видавництво: | CEUR Workshop Proceedings |
| Бібліографічний опис: | Zahorodko P. V. 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 |
| Короткий огляд (реферат): | 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. |
| Опис: | [1] Gartner, Quantum Computing Gartner Glossary, 2021. URL: https://www.gartner.com/ en/information-technology/glossary/quantum-computing. [2] K. Panetta, The CIO’s Guide to Quantum Computing, 2019. URL: https://www.gartner. com/smarterwithgartner/the-cios-guide-to-quantum-computing/. [3] J. Clark, S. Stepney, Quantum software engineering, in: Workshop on Grand Challenges for Computing Research, e-Science Institute, Edinburgh, 2002. URL: http://web.archive. org/web/20200721161705/http://www.ukcrc.org.uk/press/news/call/a5.cfm. [4] C.-H. Chenf, L.-Y. Wei, New entropy clustering analysis method based on adaptive learning, in: P. P. Wang (Ed.), Information Sciences 2007: Proceedings of the 10th Joint Conference, Salt Lake City, Utah, USA, 18–24 July 2007, 2007, pp. 1196–1202. doi:10.1142/9789812709677_0169. [5] Q-SE2020, First International Workshop on Quantum Software Engineering (Q-SE 2020) co-located with ICSE 2020, 2021. URL: https://q-se.github.io/qse2020/. [6] M. Piattini, G. Peterssen, R. Perez-Castillo, J. L. Hevia, M. A. Serrano, G. Hernández, I. G. R. de Guzmán, C. A. Paradela, M. Polo, E. Murina, L. Jiménez, J. C. Marqueño, R. Gallego, J. Tura, F. Phillipson, J. M. Murillo, A. Niño, M. Rodríguez, The Talavera Manifesto for Quantum Software Engineering and Programming, CEUR Workshop Proceedings 2561 (2020) 1–5. [7] M. Rahaman, M. M. Islam, A Review on Progress and Problems of Quantum Computing as aService (QCaas) in the Perspective of Cloud Computing, Global Journal of Computer Science and Technology: B Cloud and Distributed 15 (2015) 15 – 18. URL: https://globaljournals.org/GJCST_Volume15/3-Cloud-Data-Storage.pdf. [8] D-Wave Systems Inc, D-Wave Ocean Software Documentation, 2021. URL: https://ocean. dwavesys.com/. [9] D. Steiger, T. Häner, ProjectQ – Open Source Software for Quantum Computing, 2017. URL: https://projectq.ch/. [10] Qiskit, Qiskit, 2021. URL: https://qiskit.org/. [11] Cambridge Quantum Computing, Technology, 2020. URL: https://cambridgequantum. com/technology/. [12] Microsoft, Language-Integrated Quantum Operations: LIQUi|>, 2016. URL: https://www. microsoft.com/en-us/research/project/language-integrated-quantum-operations-liqui/. [13] Microsoft, Microsoft Quantum Documentation and Q# API Reference - Microsoft Quantum, 2021. URL: https://docs.microsoft.com/en-us/quantum/. [14] Rigetti Computing, Rigetti QCS, 2020. URL: https://qcs.rigetti.com/sdk-downloads. [15] Google, Quantum Computing Playground, 2016. URL: http://www.quantumplayground. net. [16] S. Arunachalam, R. de Wolf, A Survey of Quantum Learning Theory, 2017. arXiv:1701.06806. [17] F. Phillipson, Quantum Machine Learning: Benefits and Practical Examples, CEUR Workshop Proceedings 2561 (2020) 51–56. [18] P. Wittek, Quantum Machine Learning: What Quantum Computing Means to Data Mining, Elsevier Insights, Academic Press, San Diego, 2016. [19] V. Dunjko, P. Wittek, A non-review of Quantum Machine Learning: trends and explorations, Quantum Views 4 (2020) 17. doi:10.22331/qv-2020-03-17-32. [20] M. Pistoia, J. Gambetta, Qiskit Aqua – A Library of Quantum Algorithms and Applications, 2018. URL: https://medium.com/qiskit/ qiskit-aqua-a-library-of-quantum-algorithms-and-applications-33ecf3b36008. |
| URI (Уніфікований ідентифікатор ресурсу): | http://ceur-ws.org/Vol-2832/paper13.pdf http://elibrary.kdpu.edu.ua/xmlui/handle/123456789/4357 https://doi.org/10.31812/123456789/4357 |
| ISSN: | 1613-0073 |
| Розташовується у зібраннях: | Кафедра інформатики та прикладної математики |
Файли цього матеріалу:
| Файл | Опис | Розмір | Формат | |
|---|---|---|---|---|
| paper13.pdf | article | 881.13 kB | Adobe PDF | Переглянути/Відкрити |
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