Work

Advances in quantum machine learning

Year: 2015

Type: preprint

Abstract: Here we discuss advances in the field of quantum machine learning. The following document offers a hybrid discussion; both reviewing the field as it is currently, and suggesting directions for further research. We include both algorithms and experimental implementations in the discussion. The field's outlook is generally positive, showing significant promise. However, we believe there are appreciable hurdles to overcome before one can claim that it is a primary application of quantum computation.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.1512.02900

Authors: Adcock, Jeremy, Allen, Euan, Day, Matthew, Frick, Stefan, Hinchliff, Janna, Johnson, Mack, Morley-Short, Sam, Pallister, Sam, Price, Alasdair, Stanisic, Stasja

Institution: University of Bristol

Language: English

Topic: Quantum Computing Algorithms and Architecture

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: Defence Science and Technology Laboratory, Engineering and Physical Sciences Research Council, Defence Science and Technology Group

OpenAlex ID: W2195198640

Cites: 90

Cited by: 53

Related to: 20