2014 | OriginalPaper | Buchkapitel
Quantum Computing for Pattern Classification
verfasst von : Maria Schuld, Ilya Sinayskiy, Francesco Petruccione
Erschienen in: PRICAI 2014: Trends in Artificial Intelligence
Verlag: Springer International Publishing
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It is well known that for certain tasks, quantum computing outperforms classical computing. A growing number of contributions try to use this advantage in order to improve or extend classical machine learning algorithms by methods of quantum information theory. This paper gives a brief introduction into quantum machine learning using the example of pattern classification. We introduce a quantum pattern classification algorithm that draws on Trugenberger’s proposal for measuring the Hamming distance on a quantum computer [CA Trugenberger,
Phys Rev Let
87, 2001] and discuss its advantages using handwritten digit recognition as from the MNIST database.