A Comprehensive Survey on Quantum Machine Learning and Possible Applications

被引：8

作者：

Umer, Muhammad Junaid ^{[1
]}

Sharif, Muhammad Imran ^{[2
]}

机构：

[1] Comsats Univ Islamabad, Dept CS, Wah, Pakistan

[2] Comsats Univ Islamabad, Wah, Pakistan

来源：

INTERNATIONAL JOURNAL OF E-HEALTH AND MEDICAL COMMUNICATIONS | 2022年 / 13卷 / 05期

关键词：

Hybrid Computing; Machine Learning; Neural Networks; QML; Quantum; Quantum Algorithms; Quantum Computing; Quantum-Inspired; NEURAL-NETWORK; CLASSIFICATION; TUMOR; ENTANGLEMENT; ALGORITHMS; SEGMENTATION;

D O I：

10.4018/IJEHMC.315730

中图分类号：

R-058 [];

学科分类号：

摘要：

Machine learning is a branch of artificial intelligence that is being used at a large scale to solve science, engineering, and medical tasks. Quantum computing is an emerging technology that has a very high computational ability to solve complex problems. Classical machine learning with traditional systems has some limitations for problem-solving due to a large amount of data availability. Quantum machine learning has high performance and computational ability that can effectively be used to solve computation tasks. This study reviews the latest articles in quantum computing and quantum machine learning. Building blocks of quantum computing and different flavors of quantum algorithms are also discussed. The latest work in quantum neural networks is also presented. In the end, different possible applications of quantum computing are also discussed.

引用

页数：17

共 150 条

[1]

Adcock J, 2015, Arxiv, DOI arXiv:1512.02900

[2] Supervised learning with a quantum classifier using multi-level systems [J].