Research Area:  Machine Learning

Abstract:

The aim of this work is to give an introduction for a non-practical reader to the growing field of quantum machine learning, which is a recent discipline that combines the research areas of machine learning and quantum computing. This work presents the most notable scientific literature about quantum machine learning, starting from the basics of quantum logic to some specific elements and algorithms of quantum computing (such as QRAM, Grover and HHL), in order to allow a better understanding of latest quantum machine learning techniques. The main aspects of quantum machine learning are then covered, with detailed descriptions of some notable algorithms, such as quantum natural gradient and quantum support vector machines, up to the most recent quantum deep learning techniques, such as quantum neural networks.

Keywords:  
quantum machine learning
machine learning
QRAM
Grover
HHL
quantum support vector machine
deep learning
neural network

Author(s) Name:  Leonardo Alchieri, Davide Badalotti, Pietro Bonardi, Simone Bianco

Publisher name:  Springer

DOI:  https://doi.org/10.1007/s42484-021-00056-8

Volume Information:  Volume 3

Paper Link: https://link.springer.com/article/10.1007/s42484-021-00056-8