Machine learning in the quantum realm: The state-of-the-art, challenges, and future vision

作者：

Highlights：

• Organize the most recent research works to pave the way for QML researchers.

• Demonstrate the commonly used methods in the classification of real problems.

• Provide readers with various quantum methods to enhance classical ML.

• Present some of the challenges and future directions of QML.

摘要

•Organize the most recent research works to pave the way for QML researchers.•Demonstrate the commonly used methods in the classification of real problems.•Provide readers with various quantum methods to enhance classical ML.•Present some of the challenges and future directions of QML.

论文关键词：Quantum machine learning,Quantum computing,Quantum deep learning,Quantum inspired,Hybrid quantum–classical,Quantum classification,Variational quantum algorithms

论文评审过程：Received 16 December 2020, Revised 29 December 2021, Accepted 4 January 2022, Available online 21 January 2022, Version of Record 29 January 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.116512