@misc{10481/82332,
year = {2023},
month = {5},
url = {https://hdl.handle.net/10481/82332},
abstract = {This article gives an overview and a perspective of recent theoretical
proposals and their experimental implementations in the field of quantum
machine learning. Without an aim to being exhaustive, the article reviews
specific high-impact topics such as quantum reinforcement learning,
quantum autoencoders, and quantum memristors, and their experimental
realizations in the platforms of quantum photonics and superconducting
circuits. The field of quantum machine learning can be among the first
quantum technologies producing results that are beneficial for industry and,
in turn, to society. Therefore, it is necessary to push forward initial quantum
implementations of this technology, in noisy intermediate-scale quantum
computers, aiming for achieving fruitful calculations in machine learning that
are better than with any other current or future computing paradigm},
organization = {Junta de Andalucia	P20-00617
US-1380840},
organization = {Spanish Government	PID2019-104002GB-C21
PID2019-104002GB-C22},
publisher = {Wyley},
keywords = {Implementations of quantum information},
keywords = {Quantum artificial intelligence},
keywords = {Quantum machine learning},
keywords = {Quantum photonics},
keywords = {Quantum technologies},
keywords = {Superconducting circuits},
title = {Quantum Machine Learning Implementations: Proposals and Experiments},
doi = {10.1002/qute.202300059},
author = {Lamata, Lucas},
}