Quantum error-correcting output codes

Windridge, David ORCID logoORCID: https://orcid.org/0000-0001-5507-8516, Mengoni, Riccardo and Nagarajan, Rajagopal ORCID logoORCID: https://orcid.org/0000-0002-9724-4962 (2018) Quantum error-correcting output codes. International Journal of Quantum Information, 16 (8) . p. 1840003. ISSN 1793-6918 [Article] (doi:10.1142/s0219749918400038)

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Quantum machine learning is the aspect of quantum computing concerned with the design of algorithms capable of generalized learning from labeled training data by effectively exploiting quantum effects. Error-correcting output codes (ECOC) are a standard setting in machine learning for efficiently rendering the collective outputs of a binary classifier, such as the support vector machine, as a multi-class decision procedure. Appropriate choice of error-correcting codes further enables incorrect individual classification decisions to be effectively corrected in the composite output. In this paper, we propose an appropriate quantization of the ECOC process, based on the quantum support vector machine. We will show that, in addition to the usual benefits of quantizing machine learning, this technique leads to an exponential reduction in the number of logic gates required for effective correction of classification error.

Item Type: Article
Keywords (uncontrolled): Physics and Astronomy (miscellaneous)
Research Areas: A. > School of Science and Technology > Computer Science > Foundations of Computing group
Item ID: 24845
Notes on copyright: Electronic version of an article published as International Journal of Quantum Information, Vol. 16, No. 08, 2018, Article DOI: https://doi.org/10.1142/S0219749918400038 © 2018 World Scientific Publishing Company. Journal URL: https://www.worldscientific.com/worldscinet/ijqi
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Depositing User: Jisc Publications Router
Date Deposited: 29 Aug 2018 10:26
Last Modified: 29 Nov 2022 19:26
URI: https://eprints.mdx.ac.uk/id/eprint/24845

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