Summary of Machine Learning Applications Of Quantum Computing: a Review, by Thien Nguyen et al.
Machine Learning Applications of Quantum Computing: A Review
by Thien Nguyen, Tuomo Sipola, Jari Hautamäki
First submitted to arxiv on: 19 Jun 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Emerging Technologies (cs.ET)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This review paper bridges the gap between quantum computing and machine learning to explore their transformative impact on data processing and analysis. The authors analyze 32 seminal papers to delve into the interplay between these technologies, highlighting how they surpass classical computational methods. Quantum-enhanced methods show promise in enhancing cybersecurity, a critical sector that can benefit significantly from advancements. The review also touches on the promising implications for other sectors as the field matures. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about using quantum computers and machine learning together to do things faster and better than we could with just computers. It looks at 32 important papers in this area and finds that it’s possible to use quantum computers to make machine learning better. This can be especially helpful for cybersecurity, which needs to keep up with ever-changing threats. The paper also mentions other areas where this technology might help, like healthcare or finance. |
Keywords
» Artificial intelligence » Machine learning
