Machine Learning Applications of Quantum Computing: A Review Article Swipe
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.34190/eccws.23.1.2258
At the intersection of quantum computing and machine learning, this review paper explores the transformative impact these technologies are having on the capabilities of data processing and analysis, far surpassing the bounds of traditional computational methods. Drawing upon an in-depth analysis of 32 seminal papers, this review delves into the interplay between quantum computing and machine learning, focusing on transcending the limitations of classical computing in advanced data processing and applications. This review emphasizes the potential of quantum-enhanced methods in enhancing cybersecurity, a critical sector that stands to benefit significantly from these advancements. The literature review, primarily leveraging Science Direct as an academic database, delves into the transformative effects of quantum technologies on machine learning, drawing insights from a diverse collection of studies and scholarly articles. While the focus is primarily on the growing significance of quantum computing in cybersecurity, the review also acknowledges the promising implications for other sectors as the field matures. Our systematic approach categorizes sources based on quantum machine learning algorithms, applications, challenges, and potential future developments, uncovering that quantum computing is increasingly being implemented in practical machine learning scenarios. The review highlights advancements in quantum-enhanced machine learning algorithms and their potential applications in sectors such as cybersecurity, emphasizing the need for industry-specific solutions while considering ethical and security concerns. By presenting an overview of the current state and projecting future directions, the paper sets a foundation for ongoing research and strategic advancement in quantum machine learning.
Related Topics
- Type
- review
- Language
- en
- Landing Page
- https://doi.org/10.34190/eccws.23.1.2258
- https://papers.academic-conferences.org/index.php/eccws/article/download/2258/2192
- OA Status
- diamond
- Cited By
- 15
- Related Works
- 10
- OpenAlex ID
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4399912630Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.34190/eccws.23.1.2258Digital Object Identifier
- Title
-
Machine Learning Applications of Quantum Computing: A ReviewWork title
- Type
-
reviewOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-06-21Full publication date if available
- Authors
-
Thien Huu Nguyen, Tuomo Sipola, Jari HautamäkiList of authors in order
- Landing page
-
https://doi.org/10.34190/eccws.23.1.2258Publisher landing page
- PDF URL
-
https://papers.academic-conferences.org/index.php/eccws/article/download/2258/2192Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://papers.academic-conferences.org/index.php/eccws/article/download/2258/2192Direct OA link when available
- Concepts
-
Computer science, Quantum computer, Quantum, Artificial intelligence, Physics, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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15Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 12, 2024: 3Per-year citation counts (last 5 years)
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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