A non-review of Quantum Machine Learning: trends and explorations-Reference-Cited by-同舟云学术

A non-review of Quantum Machine Learning: trends and explorations

Published:2020-03-17 Issue: Volume:4 Page:32
ISSN:
Container-title:Quantum Views
language:en
Short-container-title:Quantum Views

Author:

Dunjko Vedran¹,Wittek Peter²³⁴⁵

Affiliation:

1. LIACS, Leiden University, Niels Bohrweg 1, 2333 CA Leiden, The Netherlands

2. Rotman School of Management, University of Toronto, Toronto, Ontario M5S 3E6, Canada

3. Creative Destruction Lab, Toronto, Ontario M5S 3E6, Canada

4. Vector Institute for Artificial Intelligence, Toronto, Ontario M5S 1M1, Canada

5. Perimeter Institute for Theoretical Physics, Waterloo, Ontario N2L 2Y5, Canada

Publisher

Verein zur Forderung des Open Access Publizierens in den Quantenwissenschaften

Reference41 articles.

1. Ewin Tang. A quantum-inspired classical algorithm for recommendation systems. In Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, STOC 2019, pages 217–228, New York, NY, USA, 2019. ACM. 10.1145/3313276.3316310.

2. Edwin Stoudenmire and David J Schwab. Supervised learning with tensor networks. In D. D. Lee, M. Sugiyama, U. V. Luxburg, I. Guyon, and R. Garnett, editors, Advances in Neural Information Processing Systems 29, pages 4799–4807. Curran Associates, Inc., 2016.

3. Hans J. Briegel and Gemma De las Cuevas. Projective simulation for artificial intelligence. Scientific Reports, 2(1), May 2012. 10.1038/srep00400.

4. Peter Wittek. Quantum Machine Learning: What Quantum Computing Means to Data Mining. Elsevier Science, 2016.

5. Maria Schuld and Francesco Petruccione. Supervised Learning with Quantum Computers. Springer International Publishing, 2018.

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